Socioeconomic Status and Mortality after Acute Myocardial Infarction

17 January 2006 | Volume 144 Issue 2 | Pages 82-93

Background: Gradients that link socioeconomic status and cardiovascular mortality have been observed in many populations, including those of countries that provide publicly funded comprehensive medical coverage. The intermediary causes of such gradients remain poorly elucidated.

Objective: To examine the relationships among socioeconomic status, other health factors, and 2-year mortality rates after acute myocardial infarction (MI).

Design: Prospective cohort study.

Setting: Ontario, Canada.

Patients: 3407 patients who were hospitalized for acute MI in 53 large-volume hospitals in Canada from December 1999 to February 2003.

Measurements: The authors obtained self-reported measures of income and education and developed profiles of the patients' prehospitalization cardiac risks and comorbid conditions. To create these profiles, the authors used the patients' self-reports and retrospectively linked no less than 12 years' worth of previous hospitalization data. Mortality rates 2 years after acute MI were examined with and without sequential risk adjustment for age, sex, ethnicity, social support, cardiovascular history and risk, comorbid conditions, and selected in-hospital process factors.

Results: Income was strongly and inversely correlated with 2-year mortality rate (crude hazard ratio for high-income vs. low-income tertile, 0.45 [95% CI, 0.35 to 0.57]; P < 0.001). However, after adjustment for age and preexisting cardiovascular events or conventional vascular risk factors, the effect of income was greatly attenuated (adjusted hazard ratio for high-income vs. low-income tertile, 0.77 [CI, 0.54 to 1.10]; P = 0.150). Noncardiovascular comorbid conditions and in-hospital process factors had negligible explanatory effect.

Limitations: Previous cardiovascular risks were ascertained through self-report or retrospectively through the longitudinal tracking of the hospitals' administrative databases. The study began with a cohort of patients who had an index cardiac event rather than with asymptomatic individuals.

Conclusions: Age, past cardiovascular events, and current vascular risk factors accounted for most of the income–mortality gradient after acute MI. This observation suggests that the "wealth–health gradient" in cardiovascular mortality may be partially ameliorated by more rigorous management of known risk factors among less affluent persons.

*For a list of members of the SESAMI Study Group, see the Appendix.

Editors' Notes Context Many studies show worse cardiovascular outcomes among poor persons than among affluent persons, but the factors that mediate this relationship are unknown. Contribution In this prospective study of 3407 Canadians who were hospitalized for myocardial infarction, 7.1% of the patients in the high-income group died within 2 years compared with 15.3% of the patients in the low-income group. Adjustment for age, preexisting cardiovascular disease, and risk factors greatly attenuated the relationship between mortality rates and income. Adjustment for other factors had little effect. Implications A history of 1 or more cardiovascular events and worse cardiovascular risk factors may explain why poor people have worse outcomes than affluent people after myocardial infarction. —The Editors

 

Author and Article Information

From the Institute for Clinical Evaluative Sciences, Sunnybrook, Women's College Health Sciences Centre, York University, Institute for Work and Health, and University of Toronto, Toronto, Ontario, Canada.

Disclaimer: The results, conclusions, and opinions are those of the authors, and no endorsement by the Ministry, the Institute, the Medical Research Council, or the Canadian Institute of Health Research is intended or should be inferred.

Acknowledgments: The authors thank Keren Fyman, Shana Kurlandsky, Talia Samson, and Wendy Cooke for their contributions to the coordination and daily operation of the study. The authors also thank the hospitals, physicians, and nurses who participated in the recruitment of patients for the Socio-Economic and Acute Myocardial Infarction study (19, 24).

Grant Support: By an operating grant from the Canadian Institutes of Health Research. The SESAMI pilot study was supported by the 1998 Michael Smith Award of Excellence from the Medical Research Council of Canada. The Institute for Clinical Evaluative Sciences is supported in part by a grant from the Ontario Ministry of Health.

Potential Financial Conflicts of Interest: Grants received: D.A. Alter (Canadian Institutes of Health Research, Heart and Stroke Foundation of Canada).

Requests for Single Reprints: David A. Alter, MD, PhD, Institute for Clinical Evaluative Sciences, 2075 Bayview Avenue, G106, Toronto, Ontario M4N 3M5, Canada; e-mail, david.alter{at}ices.on.ca.

Current Author Addresses: Drs. Alter, Austin, Williams, Morgan, and Tu, Ms. Chong, and Ms. Iron: Institute for Clinical Evaluative Services, 2075 Bayview Avenue, G106, Toronto, Ontario M4N 3M5, Canada.

Dr. Mustard: Institute for Work and Health, 481 University Avenue, Toronto, Ontario M59 2E9, Canada.

Dr. Irvine: York University, 47 Keele Street, Toronto, Ontario M3J 1P3, Canada.

Dr. Naylor: University of Toronto, 27 King's College, Toronto, Ontario M5S 1A1, Canada.

Author Contributions: Conception and design: D.A. Alter, C. Mustard, K. Iron, J. Irvine, C.D. Naylor.

Analysis and interpretation of the data: D.A. Alter, A. Chong, C.D. Naylor.

Drafting of the article: D.A. Alter.

Critical revision of the article for important intellectual content: D.A. Alter, P.C. Austin, C. Mustard, K. Iron, J.I. Williams, C.D. Morgan, J.V. Tu, J. Irvine, C.D. Naylor.

Final approval of the article: D.A. Alter, C. Mustard, J.V. Tu, C.D. Naylor.

Provision of study materials or patients: D.A. Alter, C.D. Morgan.

Statistical expertise: D.A. Alter, P.C. Austin.

Obtaining of funding: D.A. Alter, P.C. Austin, C. Mustard, K. Iron, J.I. Williams, C.D. Morgan, J.V. Tu, J. Irvine, C.D. Naylor.

Administrative, technical, or logistic support: D.A. Alter.

Collection and assembly of data: D.A. Alter, K. Iron, J.V. Tu.

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