Effects of Socioeconomic Status on Mortality after Acute Myocardial Infarction

Chang, Wei-Ching; Kaul, Padma; Westerhout, Cynthia M.; Graham, Michelle M.; Armstrong, Paul W.

doi:10.1016/j.amjmed.2006.05.056

Cited by 51 publications

(72 citation statements)

References 21 publications

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“…The use of area‐level socioeconomic exposures likely represent contextual factors of the physical and social environment such as social position, physical environment, and crime associated with health as opposed to individual‐level characteristics. Reassuringly, however, many previous studies (including some in the jurisdiction that we studied) have shown the prognostic relevance of this area‐level estimation of socioeconomic status in patients presenting with myocardial infarction 3, 6, 20, 22. Consequently, our findings highlight the contextual associations of area‐level socioeconomic factors on access to cardiac catheterization and short‐term mortality in nonmetropolitan ACS patients.…”

Section: Discussionmentioning

confidence: 80%

“…An excess risk of death has been linked to lower neighborhood income and area median household income in the setting of acute coronary syndromes (ACS),3, 4, 5, 6 in part because of barriers to timely medical care and proven evidence‐based interventions 7, 8. Several studies have shown income‐related disparities in the use of evidence‐based therapies such as invasive cardiac procedures 3, 6, 9. These disparities may lead to worse outcomes because timely receipt of these procedures improves outcomes for appropriate patients in the setting of ACS 10, 11, 12…”

Section: Introductionmentioning

confidence: 99%

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Area Median Income and Metropolitan Versus Nonmetropolitan Location of Care for Acute Coronary Syndromes: A Complex Interaction of Social Determinants

Fabreau

Leung

Southern

et al. 2016

JAHA

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BackgroundMetropolitan versus nonmetropolitan status and area median income may independently affect care for and outcomes of acute coronary syndromes. We sought to determine whether location of care modifies the association among area income, receipt of cardiac catheterization, and mortality following an acute coronary syndrome in a universal health care system.Methods and ResultsWe studied a cohort of 14 012 acute coronary syndrome patients admitted to cardiology services between April 18, 2004, and December 31, 2011, in southern Alberta, Canada. We used multivariable logistic regression to determine the odds of cardiac catheterization within 1 day and 7 days of admission and the odds of 30‐day and 1‐year mortality according to area median household income quintile for patients presenting at metropolitan and nonmetropolitan hospitals. In models adjusting for area income, patients who presented at nonmetropolitan facilities had lower adjusted odds of receiving cardiac catheterization within 1 day of admission (odds ratio 0.22, 95% CI 0.11–0.46, P<0.001). Among nonmetropolitan patients, when examined by socioeconomic status, each incremental decrease in income quintile was associated with 10% lower adjusted odds of receiving cardiac catheterization within 7 days (P<0.001) and 24% higher adjusted odds of 30‐day mortality (P=0.008) but no significant difference for 1‐year mortality (P=0.12). There were no differences in adjusted mortality among metropolitan patients.ConclusionWithin a universal health care system, the association among area income and receipt of cardiac catheterization and 30‐day mortality differed depending on the location of initial medical care for acute coronary syndromes. Care protocols are required to improve access to care and outcomes in patients from low‐income nonmetropolitan communities.

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Section: Discussionmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Area Median Income and Metropolitan Versus Nonmetropolitan Location of Care for Acute Coronary Syndromes: A Complex Interaction of Social Determinants

Fabreau

Leung

Southern

et al. 2016

JAHA

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“…Ref = reference group. (8) 7 (3) 11 (4) 9 (9) 15 (6) 13 (4) Hypertension 167 (76) 152 (64) 179 (72) 84 (80) 182 (72) 234 (69) Diabetes 55 (25) 55 (23) 58 (23) 38 (36) 64 (25) 68 ( 148 (62) 148 (60) 58 (55) 159 (63) 206 (61) Current smoking 39 (18) 55 (23) 44 (18) c 16 (15) 69 (27) 49 ( (16) 45 (19) 62 (25) 19 (18) 48 (19) 75 (22) Ejection fraction…”

Section: Figurementioning

confidence: 99%

“…[11][12][13][14][15][16][17][18][19][20][21] Given that the effects of each SES indicator can in part be either explained by or mediated through other indicators, 5 these data are incomplete. Further, most prior studies were conducted in selected populations such as clinical trial participants or women, 2,13,18 took place in different health care systems, 12,14-16,19, 21 or used administrative or registry data and lacked essential clinical details.…”

mentioning

confidence: 99%

“…Further, most prior studies were conducted in selected populations such as clinical trial participants or women, 2,13,18 took place in different health care systems, 12,14-16,19, 21 or used administrative or registry data and lacked essential clinical details. 10,12,[15][16][17]19 These limitations are important because failing to control for key clinical factors leaves substantial potential for residual confounding and thus inconclusive results. Therefore, both the internal and external validity of these results can be challenged, and their applicability to the community is uncertain.…”

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confidence: 99%

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Neighborhood Income and Individual Education: Effect on Survival After Myocardial Infarction

Gerber

Weston

Killian

et al. 2008

Mayo Clinic Proceedings

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OBJECTIVE-To evaluate the association of neighborhood-level income and individual-level education with post-myocardial infarction (MI) mortality in community patients. 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. PATIENTS AND METHODS-FromRESULTS-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,).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.Measures of social position have long been associated with post-myocardial infarction (MI) risk. 1,2 However, much of this complex interaction has yet to be elucidated. Socioeconomic status (SES) is a multidimensional construct comprising various factors acting at different levels 3-5 such that both individual-level and area-level measures could affect cardiovascular health through complementary mechanisms. 4,[6][7][8] In view of this concept, a "double jeopardy" (ie, a multidimensional vulnerability related to SES) theory was formulated but never formally tested. 9,10 Indeed, most previous studies These limitations are important because failing to control for key clinical factors leaves substantial potential for residual confounding and thus inconclusive results. Therefore, both the internal and external validity of these results can be challenged, and their applicability to the community is uncertain. 22,23Our study was undertaken to address these knowledge gaps by examining the association between primary SES indicators and post-MI mortality in patients from a geographically defined population. Specifically, we evaluated the prognostic importance of individual education and neighborhood-based income in defining risk after MI. , 2002, and May 31, 2...

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Neighborhood Income, Health Insurance, and Prehospital Delay for Myocardial Infarction

Foraker

Rose²,

McGinn

et al. 2008

Arch Intern Med

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Effects of Socioeconomic Status on Mortality after Acute Myocardial Infarction

Cited by 51 publications

References 21 publications

Area Median Income and Metropolitan Versus Nonmetropolitan Location of Care for Acute Coronary Syndromes: A Complex Interaction of Social Determinants

Area Median Income and Metropolitan Versus Nonmetropolitan Location of Care for Acute Coronary Syndromes: A Complex Interaction of Social Determinants

Neighborhood Income and Individual Education: Effect on Survival After Myocardial Infarction

Neighborhood Income, Health Insurance, and Prehospital Delay for Myocardial Infarction

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