Author + information
- Received June 10, 2002
- Revision received January 24, 2003
- Accepted February 13, 2003
- Published online June 4, 2003.
- Sunil V Rao, MD*,* (, )
- Padma Kaul, PhD*,
- L.Kristin Newby, MD, FACC*,
- A.Michael Lincoff, MD, FACC†,
- Judith Hochman, MD, FACC‡,
- Robert A Harrington, MD, FACC*,
- Daniel B Mark, MD, FACC* and
- Eric D Peterson, MD, FACC*
- ↵*Reprint requests and correspondence:
Dr. Sunil V. Rao, Duke Clinical Research Institute, P.O. Box 17969, Durham, North Carolina 27715, USA.
Objectives We sought to determine whether income-based disparities in care processes and outcome exist in patients with acute coronary syndromes.
Background Using income proxies and limited clinical data, some observational studies have shown income disparities in outcome after acute myocardial infarction (MI).
Methods Using annual household income from the economic substudy of the PURSUIT (Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin Therapy) trial, patients were grouped into low-, middle-, and high-income categories based on the U.S. Census Bureau definition of poverty. Logistic regression analysis was used to examine the association between income category and the use of cardiac procedures and the prescription of evidence-based medications at hospital discharge. Cox regression analysis was used to examine the hazard of 30-day and six-month death or recurrent MI across income categories, after adjusting for baseline characteristics.
Results Low-income patients had more chronic medical conditions and were sicker at presentation. Among low-income patients, the use of some evidence-based medications and cardiac procedures was lower and the unadjusted rates of 30-day death and six-month death or MI was higher. After multivariable adjustment, there was no consistent pattern for disparity in care processes, but the trend for higher short and intermediate-term death or MI persisted for low-income patients.
Conclusions Income level is associated with a trend toward worse outcome among patients with acute coronary syndromes. The disparity in 30-day and six-month death or MI between low and high-income patients could not be readily explained by differences in in-hospital medical or invasive treatment, suggesting that the poor outcomes may be due to differences occurring after hospital discharge.
Although the number of Americans living in poverty has decreased over the past decade, the U.S. Census Bureau reports that 11% of the population still falls below the poverty level (1). Epidemiologic studies suggest that poverty is associated with a higher incidence of ischemic heart disease (2,3)and a higher mortality after acute myocardial infarction (MI) (4–6). Proposed explanations for the relationship between income level and coronary disease include higher burden of cardiac risk factors, such as poor diet and cigarette smoking, and/or reduced access to medical care (5,7–11).
Previous studies of the relationship between income level and coronary artery disease have generally used proxies for income such as level of education (12–14), gross national product (GNP) (15), or median income of the zip code of residence (5,9)rather than directly measuring household income. In addition, many studies used population registries (4,16)or administrative data (5,9)that may have had limited clinical data.
The economic substudy of the Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin Therapy (PURSUIT) trial (17)contains self-reported income from a large subset of patients enrolled in the U.S. and presents an ideal setting in which to investigate the influence of income level on process of care and outcome. The purpose of this analysis was threefold: first, to determine the association between household income and the medical and invasive treatment of acute ischemic heart disease; second, to determine the association between household income and both the short and intermediate-term occurrence of death or recurrent MI; and third, to explore the relationship among income, processes of care, and outcomes.
The study population consisted of patients enrolled in the economic and quality of life (EQOL) substudy of the PURSUIT trial. Details of the trial methods have been published previously (18). Briefly, the PURSUIT trial (n = 10,498) randomized patients with unstable angina or non–Q-wave MI to either eptifibatide or placebo. Patients were eligible if they had ischemic chest pain within the prior 24 h, and transient electrocardiographic changes or elevated markers of myocardial necrosis. Concomitant medical therapy, including aspirin, and cardiac procedures were left to the discretion of the treating physician. The EQOL substudy of patients randomized in the U.S. (n = 3,522) was prospectively conducted concurrent with the main PURSUIT investigation (17). A random sample consisting of 70% of patients enrolled in the U.S. (n = 2,464) were enrolled. Patients in the substudy were asked to complete a questionnaire that contained self-reported annual household income in addition to other questions regarding activities of daily living and functional status. Patients checked one of six boxes on the questionnaire that corresponded to their annual household income: <$10,000; $10,001 to $20,000; $20,001 to $30,000; $30,001 to $45,000; $45,001 to $60,000; and >$60,000.
Definitions and end points
The U.S. Census Bureau defines poverty based on a set of income thresholds that vary by family size. Only pretax income is considered, and families or individuals with income below the corresponding poverty threshold are considered to be poor. For the purposes of this study, we defined three income categories based on self-reported annual household income: <$20,000 (low-income), $20,000 to $60,000 (middle-income), and >$60,000 (high-income). A cutoff of $20,000 was used to define the lowest income group because this corresponds approximately to twice the “Weighted Average Poverty Threshold” used by the Census Bureau in 1995 to define poverty for householders aged 65 or older.
The main outcome measures were the occurrence of death or MI at 30 days and six months. The occurrence of MI at 30 days was defined as new chest pain and ST-segment elevation within 18 h of enrollment, new or repeat creatine kinase-MB fraction (CK-MB) elevation above upper limit of normal after 18 h, or CK-MB elevation above three times the upper limit of normal after percutaneous coronary intervention (PCI) and above five times the upper limit of normal after coronary artery bypass graft (CABG) surgery (18). All suspected infarctions and deaths occurring between enrollment and 30 days were evaluated by a masked clinical events committee. Events occurring between 30 days and six months were assessed from hospital discharge summaries and death certificates.
We compared baseline patient characteristics across the three income categories using chi-square tests for categorical variables and the nonparametric Kruskal-Wallis tests for continuous variables. A value of p < 0.05 was considered significant. Univariate and multivariable logistic regression analyses were used to examine the association between income category and the use of cardiac procedures within 30 days of enrollment and prescription of evidence-based medications at discharge from the index hospitalization. Specifically, models were developed to examine the independent association between income and the use of cardiac catheterization, PCI, CABG, as well as prescription of aspirin, beta-blockers, angiotensin-converting enzyme (ACE) inhibitors, and lipid-lowering medications, after adjusting for key baseline variables such as age, gender, race, hypertension, diabetes, congestive heart failure, peripheral vascular disease, and MI at enrollment. Odds ratios and 95% confidence intervals were generated for the low-income group using the high-income group as the reference and were converted to relative risks using the method of Zhang and Yu (19).
Kaplan-Meier analysis was used to examine six-month survival free of recurrent MI across income categories. Survival curves were compared using the log-rank test statistic. Cox regression analysis was used to calculate baseline-adjusted hazard of 30-day and six-month death or recurrent MI across income categories. A comprehensive set of variables found to be significantly associated with 30-day death/recurrent MI in a previously published model based on the entire PURSUIT cohort (20)were included in a backward stepwise model. These included age, gender, weight, height, diabetes, smoking status, worst Canadian Cardiovascular Society class in the last six weeks, peripheral vascular disease, prior beta-blocker use, prior calcium channel blocker use, prior use of nitrates, systolic blood pressure, diastolic blood pressure, rales, presence of ST-segment depression >0.5 mm, time to treatment, and treatment with eptifibatide. Income category was forced into the models to examine the relative hazard of death or recurrent MI among low-income patients compared to high-income patients.
Ethics of protocol
The Institutional Review Boards of all participating institutions reviewed and approved the protocols of the PURSUIT trial. All patients enrolled gave written informed consent for the collection of financial and resource-use data.
Of the 2,464 patients in the U.S. EQOL substudy of the PURSUIT trial, 2,207 (90%) had completed self-reported income data and six-month follow-up, and they constitute the current study’s patient population. No significant differences existed in baseline characteristics of patients included in the study and in the overall U.S. cohort. Based on our definition of income categories, 1,000 (45%) of the study patients were classified as low-income; 952 (43%) as middle-income; and 255 (12%) as high-income. Table 1shows the baseline clinical characteristics of the patients across the three income groups. Patients in the low-income category were older and more likely to be women, black, and living alone. There was also a higher prevalence of risk factors for heart disease such as hypertension, diabetes, prior CABG, and prior congestive heart failure among low-income patients. Upon presentation, they were more likely to have ST-segment depression and evidence of pulmonary edema, and they had slightly longer time from symptom onset to randomization (p = 0.09).
As shown in Table 2, the rates of evidence-based medical therapy prescribed at hospital discharge varied among the income groups. There was lower use of aspirin and beta-blockers in the low-income patients compared with the middle-income patients. Compared with both the middle- and high-income patients, low-income patients had a lower rate of lipid-lowering drugs prescribed at discharge (27.0% for low-income; 32.2% for middle-income; 36.1% for high-income, p < 0.01) but higher rates of ACE inhibitors (32.9% for low-income; 24.1% for middle-income; 22.4% for high-income, p < 0.01). With regard to procedures, significantly fewer low-income patients underwent cardiac catheterization and PCI, but no differences were seen among the income groups with respect to CABG (Table 2). The analysis was repeated using an income cutoff of <$10,000 to define low-income, and it produced similar results.
To account for the effect of older age among the poor, a separate analysis stratified by age was performed. Among patients younger than age 65, a trend was seen toward a lower rate of evidence-based medical therapy (e.g., beta-blockers and lipid-lowering agents) in the low-income group (Table 3). Significantly more low-income patients received ACE inhibitors. Significantly fewer low-income patients underwent cardiac catheterization or PCI. No difference existed in the rate of CABG across the income groups. In the patients older than 65 years, significantly fewer low-income patients received aspirin (81.3% for low-income; 87.5% for middle-income; 93.0% for high-income, p < 0.05), beta-blockers (56.5% for low-income; 64.0% for middle-income; 68.4% for high-income, p < 0.05), and lipid-lowering agents (23.8% for low-income; 30.4% for middle-income; 36.8% for high-income, p < 0.05). More middle-income patients underwent cardiac catheterization and PCI, but again there was no difference in the rate of CABG across the income groups.
The unadjusted rate of death or MI at 30 days was higher in the low-income group, although this was not statistically significant (Table 2). When the components of the composite end point were examined separately, significantly higher 30-day mortality was seen among the low-income patients (3.5% for low-income; 1.9% for middle-income; 0.4% for high-income group, p < 0.01). At six-months, the unadjusted rates of both the composite end point and death alone were significantly higher in the low-income group (5.6% for low-income; 3.3% for middle-income; 1.6% for high-income, p < 0.01) (Table 4). Similar results were seen when an income cutoff of <$10,000 was used to define low-income category.
The rates of the composite six-month end point as well as its individual components were higher than the 30-day end point. Figure 1shows the Kaplan-Meier rates of MI-free survival at six months for the three income groups. The curves separated within 30 days and continued to separate up to six months of follow-up.
Again, an analysis stratified by age showed a trend toward higher 30-day death or MI and six-month death or MI in the low-income groups regardless of age (Table 3).
Table 4shows the adjusted relative risks of aspirin, beta-blocker, ACE inhibitor, and lipid-lowering agent prescription at discharge, as well as procedures by 30 days for the low-income group. After adjustment for baseline characteristics, there did not appear to be any pattern of disparity in care processes for the low-income patients relative to the high-income patients. However, the trend toward a higher risk of death or recurrent MI at 30 days and six months persisted for the low-income group after adjustment. Using an income cutoff of <$10,000 to define low-income produced identical results.
The results of this study indicate that poverty is associated with a trend toward worse short- and intermediate-term outcomes among patients with non–ST-segment elevation acute coronary syndromes. As income level decreased, the risk of 30-day and six-month death or MI increased. Interestingly, this occurred despite the apparent lack of differences in either revascularization or medical therapy at the time of hospital discharge. The rates of some evidence-based medical therapies (like lipid-lowering agents) were generally lower among the poor, but the use of other therapies (such as ACE inhibitors) was higher. Lower income level was associated with lower use of cardiac catheterization and PCI, but higher rates of CABG. None of these associations were statistically significant after controlling for baseline risk factors. Although no longer statistically significant, the trend toward a worse outcome persisted among the poor after adjustment for baseline differences among the income groups. Furthermore, the six-month outcomes appeared to be worse than the 30-day outcomes for low-income compared with high-income patients.
Our study is one of few that have examined the issue of income in the setting of a clinical trial. Shibata and colleagues (15)examined country-specific mortality rates from five international randomized clinical trials of acute ST-elevation MI. Using a country’s GNP as a proxy for income, they found an inverse linear relationship between GNP and mortality from MI. Evidence for differences in care processes in a clinical trial comes from a study by Cohen et al. (21), who examined the rates of coronary angiography, coronary angioplasty, and bypass surgery in Latin America among patients enrolled in the PURSUIT trial. They found that patients enrolled in Latin America were less likely to receive cardiac procedures and had higher mortality than did patients enrolled outside of Latin America. The lack of disparity in medical and invasive therapy among the U.S. patients enrolled in the PURSUIT trial suggests that, in the U.S., process of care may be more equitable for patients involved in clinical trials.
Other observational studies have found lower rates of both evidence-based medical therapy (9)and cardiac procedures (5)among the poor. Rathore et al. (9)found that elderly patients residing in areas in the U.S. where the median income was less than the lowest 15th percentile of U.S. incomes were less likely to receive reperfusion therapy, aspirin at admission and during hospitalization, and beta-blockers at hospital discharge even when they were considered to be “ideal” candidates for these therapies. Among patients older than 65 years, we found a similar pattern of lower aspirin, beta-blocker, ACE inhibitor, and lipid-lowering agent use in low-income patients.
Using administrative data from Canada and geographic proxies for income, Alter et al. (5)found a direct relationship between socioeconomic status (SES) and access to coronary angiography and revascularization procedures, and an inverse relationship between SES and mortality from acute MI. In our age-stratified analysis, significantly fewer low-income patients younger than age 65 underwent cardiac catheterization and PCI. Among patients older than age 65, however, we were unable to find any consistent pattern of disparity in revascularization procedures by income level. This pattern of lower use of evidence-based medical therapy but similar rates of procedures may be due to federal coverage of procedures for patients 65 years and older in the U.S. through the Medicare entitlement.
The aforementioned observational studies provide valuable information on the association between income level and process of care, but they have two major limitations. First, administrative databases may have limited clinical information. Our study was performed using data from a clinical trial where data collection is rigorous. Second, these observational studies all used proxies for income such as median income of the neighborhood of residence, GNP of the country of origin, or education level. These measures provide important, but indirect, data on personal income, and may suffer from the “ecologic fallacy” of misclassifying income level on the basis of geographic economic factors, which can lead to substantial measurement error (22,23). To avoid this pitfall, we used patients’ self-reported income and found that lower household income level was associated with generally higher short- and intermediate-term death or recurrent MI.
This was present despite the lack of association between low income and lower use of procedures in the inpatient setting or medical therapy at discharge. Other potential mechanisms by which poverty is associated with adverse outcomes include differences in patient or community characteristics. Patient-level differences can occur at multiple levels, from health status to medication compliance and insurance coverage. The poor had higher rates of hypertension, diabetes, and prior congestive heart failure, which can reflect either lack of medical care prior to admission or the effect of poverty itself. For example, low SES has been associated with lower rates of exercise and higher rates of smoking, and higher lipid levels and higher blood pressure (24).
In addition, the poor are intuitively less able to afford prescription drugs, which can lead to suboptimal compliance with discharge medications. Although many types of healthcare insurance (including Medicaid in many states) provide medication coverage, a greater proportion of patients in the low-income group were Medicare beneficiaries. The Medicare program does not currently provide medication coverage, and it is unknown whether the provision of a drug benefit would increase compliance and improve outcomes among the elderly poor. Community-level differences may also explain the widened gap between 30-day and six-month mortality (25). Neighborhoods may differ in access to medical care facilities, the number of advertisements for tobacco products (26), and safety. All these factors, alone or in concert, may explain the association between low income and adverse events after hospital discharge.
There are some limitations to our study. First, patients who were poor were older than were patients in the other income groups, and it is possible that the disparities in outcome were driven to a large extent by age. However, after age stratification and adjustment for clinical characteristics, the mortality differences persisted in low-income patients older than age 65. Second, we did not examine the effect of income level on compliance with discharge medications, which may be responsible for the increased death and recurrent MI among low-income patients seen at six months. Further research is needed to determine the differences among income groups in the outpatient setting, including differences in compliance, social support, and access to primary care. Third, our study did not have the statistical power to examine the effect of different insurance coverage on care processes or outcome. Fourth, the lack of racial heterogeneity in our sample precluded our ability to examine an interaction between income and race. Finally, our study cohort was comprised of participants in a clinical trial; therefore, our results may not be applicable to the general population of patients with acute coronary syndromes.
In conclusion, our study indicates that poverty, measured as household income, is associated with a generally worse outcome in patients with non–ST-segment elevation acute coronary syndromes. The trend toward a higher risk of short- and intermediate-term death or recurrent MI among low-income patients was present despite the lack of income-related differences in inpatient care processes such as cardiac procedures and prescription of evidence-based medicines at hospital discharge. A number of postdischarge factors, rather than in-hospital care, may be responsible. More study is needed to determine whether disparities in follow-up care after hospital discharge, medication compliance, social support, or a combination of these factors account for the worse outcomes among the poor.
☆ This work was supported in part by a grant from COR Therapeutics, Inc., South San Francisco, California, and Key-Schering-Plough, Inc., Kenilworth, New Jersey (now Millennium Pharmaceuticals, Inc., Cambridge, Massachusetts).
- angiotensin-converting enzyme
- coronary artery bypass graft surgery
- creatine kinase-MB fraction
- economic and quality of life
- gross national product
- myocardial infarction
- percutaneous coronary intervention
- Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin Therapy trial
- socioeconomic status
- Received June 10, 2002.
- Revision received January 24, 2003.
- Accepted February 13, 2003.
- American College of Cardiology Foundation
- ↵Dalaker, J. Poverty in the United States: 2000. P60-214. 2001. Washington, DC: U.S. Census Bureau. Current Population Reports
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