Abstract
Background
Sex and neighborhood socioeconomic status (nSES) may independently affect the care and outcomes of acute coronary syndromes (ACS), partly through barriers in timely access to cardiac catheterization. We sought to determine whether sex modifies the association between nSES, and the receipt of cardiac catheterization and mortality following an ACS in a universal healthcare system.
Methods and Results
We studied 14,012 ACS patients admitted to cardiology services between April 18, 2004 and December 31, 2011 in Southern Alberta, Canada. We used multivariable logistic regression to compare the odds of cardiac catheterization within 2 and 30 days of admission and the odds of 30-day and 1-year mortality for men and women by quintile of neighborhood median household income. Significant relationships between nSES and the receipt of cardiac catheterization and mortality after ACS were detected for women but not men. When examined by nSES, each incremental decrease in neighborhood income quintile for women was associated with a 6% lower odds of receiving cardiac catheterization within 30 days (p=0.01) and a 14% higher odds of 30-day mortality (p=0.03). For men, each decrease in neighborhood income quintile was associated with a 2% lower odds of receiving catheterization within 30 days (p=0.10), and a 5% higher odds of 30-day mortality (p=0.36).
Conclusions
Associations between nSES and receipt of cardiac catheterization and 30-day mortality were noted for women but not men in a universal healthcare system. Care protocols designed to improve equity of access to care and outcomes are required, especially for low-income women.
Keywords: myocardial infarction, socioeconomic status, gender, angiography, mortality
Cardiovascular disease is a leading cause of morbidity and mortality for women.1,2 Although the overall prevalence of coronary artery disease (CAD) is higher in men, increased attention has been devoted to the clinical impacts and outcomes of CAD among women.3–5 This focus has been partly fuelled by reports highlighting lower receipt of evidence-based care for women, such as access to cardiac catheterization and percutaneous coronary interventions in the setting of acute coronary syndromes (ACS).6–10 Moreover, higher mortality and complication rates described in the setting of ACS for women, particularly younger women, may in part be due to disparities in care,11–17 given that timely receipt of these procedures improves outcomes in the setting of an ACS for appropriate patients.18–20
Lower neighborhood socioeconomic status (nSES) has also been linked to barriers to timely medical care and evidence-based therapies,21–23 as well as excess risk of death in the setting of ACS.23–25 Moreover, many women still face an economic disadvantage in society, with income differentially distributed among men and women.26,27 Additionally, recent evidence among patients with premature ACS has shown increased clustering of traditional and non-traditional cardiovascular risk factors such as depression and chronic stress in low-income women that may contribute to income gradients in care and outcomes for women but not men.28 Despite differential distribution by sex of nSES and cardiovascular risk factors, as well as ACS-related mortality and complication rates, few studies have examined whether sex modifies how nSES factors are associated with access to cardiac catheterization and outcomes of ACS. Furthermore, it is unknown whether the previously described income gradients in access to cardiac catheterization and mortality in the setting of ACS persist in a universal healthcare system and whether they are differentially present among women relative to men.
We hypothesized that sex and nSES disparities in access to catheterization and mortality after ACS persist, and that sex modifies the association of nSES with these outcomes such that income gradients are more pronounced among women. We examined this relationship in Canada where the universal healthcare system aims to provide equitable care with prioritization based on medical necessity. As such, health insurance status is not an explanatory variable in our evaluation of sex and SES factors as determinants of care and outcomes.
Methods
Study Setting and Data Sources
This cohort study was conducted in two Southern Health Zones of the province of Alberta, Canada with an approximate catchment population of 1.7 million people. Data were obtained through the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH) database, a provincial clinical registry with essentially complete ascertainment of all patients admitted to a cardiac service and/or receiving coronary angiography since 2004.29 One of the main strengths of this registry is that demographic, clinical, and procedural information is prospectively collected using standardized definitions with trained data abstractors and validated methods to ensure a rich collection of accurate, clinical data.29 For income and mortality data, we performed linkages with the 2006 Canadian Census and the Alberta Bureau of Vital Statistics as previously described.30,31 In total, 33 acute care facilities (including hospitals, cardiology facilities, and urgent care centers) were included in our study. Facility address location information was obtained from Alberta Health Services (www.albertahealthservices.ca).
Study Population
Our cohort included Alberta residents, 18 to 99 years of age, admitted to any cardiac service in the two Southern health zones between April 18, 2004 and December 31, 2011 with a principal diagnosis of an ACS (ST-elevation myocardial infarction [STEMI], Non-ST-elevation myocardial infarction [NSTEMI] and unstable angina [UA]) at the time of discharge or admission (if discharge diagnosis was missing). Vital statistics and catheterization data were essentially complete for patients from Alberta, as such patients were followed from admission until death or a maximum of 1 year with a study end date of December 31, 2012. To avoid confounding of the outcomes of interest by different admissions only the first admission was included for patients with multiple admissions for an ACS during the study period. We excluded patients if census data were unavailable. Patients residing outside of the two Southern Alberta health zones were also excluded.
Study Variables
Patient sex was accurately determined from the APPROACH database, with no missing values. Throughout the paper, we refer to a combination of “sex factors”, recognizing that constructs of sex and gender are biological and sociological constructs, respectively, that define men and women.32 Both sex and gender may underlie differences between men and women in access to catheterization and outcomes after ACS. As such, we intentionally refer to ‘sex’ in a manner recognizing that differences between men and women described in our results likely arise from a combination of both sex (biological) and gender (psychosocial) factors.32 The other main construct of interest in our study, nSES, was described using the validated nSES dimension of neighborhood-level median household income, determined using postal code information as in previous studies.30,31
We assessed the receipt of cardiac catheterization immediately before admission to 2 days after presentation (defined as emergent) and within 30 days of presentation (defined as urgent), based on the current evidence and guidelines for use of these procedures in the setting of ACS.18,19 We assessed all-cause mortality within 30 days and 1 year of admission.
Data were collected for age, sex, type of ACS (STEMI, NSTEMI and UA), prior diagnosis of coronary artery disease (CAD), hypertension, dyslipidemia, diabetes, current and former smoking status, prior ACS, prior coronary revascularization procedure, family history of coronary artery disease, congestive heart failure, chronic lung disease, peripheral vascular disease, chronic renal disease, dialysis, cerebrovascular disease, cancer, gastrointestinal disease, and liver disease. Additionally, the geographic location of the medical facility of presentation was determined by the location of the first recorded presentation for ACS admission. Overland distances to the cardiac catheterization facility were calculated in kilometers by geocoding medical facility addresses using Google Maps™, an online geographic information systems mapping program maintained by Google (Mountain View, CA).33,34 Missing data on comorbidities were obtained using a validated data merging method that draws on the Canadian national Discharge Abstract Database, as previously described.35
Statistical Analysis
Descriptive statistics were reported according to neighborhood median household income quintiles for both men and women. Differences in demographic, clinical characteristics and unadjusted outcomes between men and women were compared using the Chi-square test for categorical variables and the Student’s t-test for continuous variables. Differences across neighborhood income quintiles for each sex were compared using the Chi-square test for trend for categorical variables and ANOVA or the non-parametric Kruskal-Wallis test (where appropriate) for continuous variables.
We first compared the adjusted odds of the outcomes of interest for women vs. men by using logistic regression models with nSES and all demographic and clinical characteristics in Table 1 included as covariates in the models. To examine the combined effects of sex and nSES, we then categorized patients into one of ten subgroups defined by sex and neighborhood income quintile. We compared the adjusted odds of catheterization or mortality for each subgroup vs. the highest neighborhood income men (reference group) using logistic regression models adjusting for all clinical and demographic covariates. We used this strategy to examine for additive associations of sex and nSES in our models without making any other a priori assumptions about the distributional relationship between sex and income on the predefined outcomes of interest. We then assessed for collinearity (defined as a change in the standard error by >10%); when present, these variables were excluded from the final model unless there was statistical evidence for confounding (defined by a change in the beta-coefficient for the variables of interest by >20%). From our exploration of collinearity, the variables for “family history of coronary artery disease, non-metropolitan status and teaching hospital” were excluded from the adjusted models.
Table 1.
Cohort Characteristics by Sex and Income Quintile.
| Variable | Sex | Averages by Sex |
P-value† | Neighborhood Median Household Income Quintile | |||||
|---|---|---|---|---|---|---|---|---|---|
| 1 (lowest) (N=2635) |
2 (N=2766) |
3 (N=2766) |
4 (N=2896) |
5 (highest) (N=2949) |
P-value for Trend†† |
||||
| Median Household Income (IQR $CAD)* | Men | 63,878 [48,779 – 84,174] | <0.001 | 38,701 [34,061 – 42,425] | 49,706 [47,107 – 52272] | 60,708 [57,878 – 65,397] | 75,846 [72,562 – 81,667] | 103,190 [94,901 – 117,628] | - |
| Women | 58,570 [45,865 – 77,690] | 38,581 [33,168 – 42,310] | 49,361 [46,664 – 51,998] | 60,754 [57,656 – 64,641] | 75,638 [72,217 – 80,812] | 103,326 [95,675 – 118,630] | - | ||
| Clinical Characteristics | |||||||||
| Mean Age – years (SD) | Men | 63.0 (12.6) | <0.001 | 64.1 (12.8) | 63.6 (12.5) | 63.6 (12.9) | 62.2 (12.6) | 61.9 (11.9) | <0.001 |
| Women | 68.4 (12.9) | 70.3 (13.1) | 68.6 (13.1) | 68.3 (12.0) | 67.4 (13.2) | 66.9 (13.2) | <0.001 | ||
| Non-Metropolitan – % | Men | 22.4 | 0.31 | 36.7 | 37.2 | 20 | 14.9 | 7.8 | <0.001 |
| Women | 23.2 | 34.4 | 36.6 | 21.1 | 14.4 | 4.1 | <0.001 | ||
| Dyslipidemia – % | Men | 75.9 | <0.001 | 76 | 76.2 | 77.9 | 75 | 74.3 | 0.086 |
| Women | 69.6 | 69.8 | 73.4 | 71.3 | 66.4 | 66.6 | 0.01 | ||
| Hypertension – % | Men | 67.2 | <0.001 | 68.6 | 68 | 68.3 | 65.9 | 65.7 | 0.02 |
| Women | 74.3 | 78.1 | 76.2 | 72.3 | 73.5 | 70 | <0.001 | ||
| Diabetes Mellitus – % | Men | 25.3 | 0.52 | 27.3 | 28.1 | 25.6 | 25.6 | 21 | <0.001 |
| Women | 25.8 | 27.2 | 27.2 | 28 | 25.3 | 20.7 | 0.004 | ||
| Current Smoker – % | Men | 28.7 | <0.001 | 35.1 | 32.8 | 30.7 | 26.8 | 20.4 | <0.001 |
| Women | 22.7 | 26.2 | 25.8 | 23.6 | 19.9 | 16.6 | <0.001 | ||
| Prior Acute Coronary Syndrome – % | Men | 23.9 | <0.001 | 27.7 | 25.8 | 25.1 | 22.5 | 19.8 | <0.001 |
| Women | 19.2 | 21.8 | 22.3 | 19.9 | 15 | 16 | <0.001 | ||
| Prior PCI* – % | Men | 23.4 | <0.001 | 24.8 | 22.7 | 24.1 | 23.8 | 22 | 0.13 |
| Women | 17.4 | 18.4 | 17.9 | 19.2 | 16 | 15.3 | 0.06 | ||
| Prior CABG* – % | Men | 9.2 | <0.001 | 9.5 | 9.5 | 10 | 8.9 | 8.1 | 0.08 |
| Women | 5.8 | 6.4 | 6 | 6 | 5.2 | 5 | 0.16 | ||
| Congestive Heart Failure – % | Men | 11.5 | <0.001 | 15.5 | 12.4 | 11.7 | 10 | 9.1 | <0.001 |
| Women | 16.4 | 18.9 | 17.2 | 18.1 | 14.2 | 12.7 | <0.001 | ||
| Cerebrovascular Disease – % | Men | 7.3 | <0.001 | 8.8 | 7.4 | 7.8 | 7.6 | 5.3 | <0.001 |
| Women | 9.6 | 10.7 | 11.4 | 8.6 | 9.3 | 7.3 | 0.007 | ||
| Peripheral Vascular Disease – % | Men | 5.3 | 0.004 | 7.8 | 6.3 | 5.5 | 4.5 | 2.9 | <0.001 |
| Women | 6.5 | 7.6 | 6.7 | 6.9 | 6.2 | 4.9 | 0.04 | ||
| Renal Disease – % | Men | 4.9 | 0.15 | 6 | 5.8 | 5.7 | 4.3 | 3.3 | <0.001 |
| Women | 5.5 | 6.4 | 5.6 | 6.5 | 4.3 | 4.4 | 0.04 | ||
| Dialysis – % | Men | 1.3 | 0.56 | 1.9 | 1.1 | 1.5 | 0.9 | 1.1 | 0.02 |
| Women | 1.4 | 1.2 | 1.4 | 1.5 | 1.3 | 1.6 | 0.67 | ||
| Chronic Lung Disease – % | Men | 13.3 | <0.001 | 17.8 | 14.8 | 14.3 | 10.9 | 10.1 | <0.001 |
| Women | 17.2 | 20.5 | 17.5 | 17.1 | 16.5 | 13.3 | <0.001 | ||
| Liver or Gastrointestinal Disease – % | Men | 8.2 | <0.001 | 10 | 7.9 | 9.1 | 7 | 7.2 | <0.001 |
| Women | 10.7 | 13.3 | 12.9 | 9.7 | 9.2 | 7.7 | <0.001 | ||
| Malignancy – % | Men | 4.7 | 0.18 | 5.1 | 4.9 | 4.8 | 3.9 | 4.8 | 0.31 |
| Women | 5.2 | 5.5 | 5.2 | 4.2 | 6.3 | 4.7 | 0.85 | ||
| ACS Type | |||||||||
| STEMI* – % | Men | 32.5 | <0.001 | 32.3 | 33.4 | 33.9 | 31 | 32 | 0.35 |
| Women | 25.6 | 27.1 | 25.7 | 27.8 | 24.6 | 22 | 0.03 | ||
| NSTEMI* – % | Men | 34 | 0.005 | 36.3 | 35.8 | 33.8 | 32.8 | 31.9 | <0.001 |
| Women | 36.5 | 38.7 | 36.9 | 35.4 | 36.7 | 34 | 0.07 | ||
| Unstable Angina – % | Men | 33.6 | <0.001 | 31.5 | 30.8 | 32.3 | 36.1 | 36.2 | <0.001 |
| Women | 38 | 34.2 | 37.4 | 36.8 | 38.7 | 44.1 | <0.001 | ||
| Characteristics of Initial Presenting Facility | |||||||||
| Teaching Hospital – % | Men | 76.3 | 0.95 | 61.9 | 61.9 | 79.1 | 83.6 | 90.2 | <0.001 |
| Women | 76.3 | 65.1 | 63 | 78.4 | 84.8 | 95.3 | <0.001 | ||
| Median [IQR]* Distance (km) of Initial Facility to Catheterization Lab | Men | 11.8 [0 – 12.2] | 0.01 | 11.8 [0 – 221] | 12.2 [0 – 221] | 11.8 [0 – 12.2] | 7.3 [0 – 12.2] | 0 [0 – 11.8] | <0.001 |
| Women | 11.8 [0 – 12.2] | 11.8 [0 – 221] | 12.2 [0 – 221] | 11.8 [0 – 12.2] | 11.8 [0 – 12.2] | 0 [0 – 11.8] | <0.001 | ||
IQR = Interquartile range, $CAD = Canadian Dollars, SD = standard deviation, PCI = percutaneous coronary intervention, CABG = coronary artery bypass graft, STEMI = ST-segment elevation myocardial infarction, and NSTEMI = Non-ST-segment elevation myocardial infarction, km = kilometers,
P-Value from Chi-Square or T-test,
P-Value from Chi-Square Trend Test
Given the visual appearance of the additive associations of sex and nSES on the outcomes of interest and to estimate sex-specific neighborhood income gradients, we chose to re-specify neighborhood income quintile as a continuous predictor, assuming a linear relationship between income and the outcomes of interest for both men and women. We modeled the association of each incremental decrease in neighborhood income quintile for each sex compared to men and women of the corresponding highest neighborhood income quintile on the receipt of catheterization and mortality. We then formally tested for effect modification by sex by including an interaction term between neighborhood income and sex. We accounted for clustering at the facility level in our logistic regression models and unadjusted comparisons of the outcomes of interest using generalized estimating equations with a working correlation matrix initially assuming independence. Additionally, we accounted for temporal trends by adding indicator variables to our models for each calendar year of the study from 2004 to 2011 inclusively.
All analyses were performed using SAS statistical software, version 9.3 (SAS Institute, Inc., Cary, North Carolina). We reported two-tailed P values (with a predefined threshold for statistical significance of <0.05) or 95% confidence intervals when appropriate. Approval for this study was received from the University of Calgary Conjoint Health Research Ethics Board and the Harvard Medical School Institutional Review Board.
Results
Baseline Characteristics
We identified 21,028 admissions for ACS among adult patients in the two Southern Alberta health zones. Among these admissions, 5398 episodes were excluded as repeat admissions for ACS. A further 1618 (10.3%) admissions were excluded because of missing neighborhood income data of which 372 (23%) were women. The final study cohort of 14,012 adult patients included 4017 women and 9995 men.
Baseline demographic and clinical characteristics are presented in Table 1. Median neighborhood household incomes ranged from $38,701 CAD in the lowest neighborhood income quintile (Quintile 1) to $103,190 CAD in the highest neighborhood income quintile (Quintile 5). Women, on average, were from lower income areas than men ($58,570 CAD vs. $63,878 CAD; p<0.001). Consistent with this finding, the distribution of men and women patients by neighborhood income quintiles revealed a larger proportion of women vs. men in lower income areas (22.1% vs. 17.5% in the lowest neighborhood income quintile, p<0.001) and alternatively more men in higher income areas (22.5% vs. 17.5% in the highest neighborhood income quintile, p<0.001).
Compared with men, women were typically older by five years (63 vs. 68.4 years; p<0.001), less likely to be current smokers or have dyslipidemia, and more likely to have common medical comorbidities such as hypertension, congestive heart failure, cerebrovascular disease, renal disease and chronic lung disease (Table 1). Additionally, women were more likely than men to present with NSTEMI and UA and less likely to present with STEMI. Men were more likely than women to have been previously diagnosed with ACS and receive a prior percutaneous coronary intervention (23.4% vs.17.4%; p<0.001) or coronary artery bypass grafting (9.2% vs. 5.8%; p<0.001).
Across neighborhood income quintiles for both men and women, subjects in lower income quintiles compared to higher income quintiles were typically older, more likely to present initially to a non-metropolitan facility and had higher rates of medical comorbidities such as diabetes, smoking, congestive heart failure, cerebrovascular disease and chronic lung disease; a larger proportion of these patients had a history of previous ACS (Table 1). For both men and women, patients in the highest neighborhood income quintile were more likely to present with unstable angina, whereas NSTEMI was more common among those from lower income neighborhoods. Both men and women in the lowest neighborhood income quintiles were more likely to present to a medical facility further from the academic facility with on-site catheterization capability (Median distance 11.8 km vs. 0 km; P<0.001).
Unadjusted Rates of Cardiac Catheterization and Mortality
Table 2 presents unadjusted rates for cardiac catheterization and mortality for men and women and also for each sex stratified by neighborhood income quintile. Among women, those from lower income areas had higher rates of 30-day but not 1-year mortality than women from higher income areas (tests for trend; p=0.01, and p=0.06 respectively) (Table 2). Among men, significant mortality differences were detected at 30 days (test for trend; p=0.04), and 1-year (test for trend; p<0.001), where men from lower income areas were observed to have excess mortality compared to those residing in higher income areas (Table 2).
Table 2.
Unadjusted comparisons by sex and income quintile
| Outcomes | Sex | Average by Sex % |
P-Value† | Neighborhood Median Household Income Quintile and Sex | |||||
|---|---|---|---|---|---|---|---|---|---|
| Quintile 1 (lowest) |
Quintile 2 | Quintile 3 | Quintile 4 | Quintile 5 (highest) |
P-Value for trend†† |
||||
| % Men N = 1749 |
% Men N = 1895 |
% Men N = 1983 |
% Men N = 2120 |
% Men N = 2248 |
|||||
| % Women N = 886 |
% Women N = 871 |
% Women N = 783 |
% Women N = 776 |
% Women N = 701 |
|||||
| Catheterization* Within 2 days – % | Men | 40.5 | <0.001 | 35.7 | 38.9 | 41.5 | 40.9 | 44.5 | 0.06 |
| Women | 30.8 | 26.5 | 29.2 | 31.7 | 33.6 | 34.4 | 0.09 | ||
| Catheterization* Within 30 days – % | Men | 71.7 | <0.001 | 68.8 | 73 | 71.1 | 71.3 | 73.9 | 0.002 |
| Women | 62.1 | 57.9 | 61.7 | 62.8 | 63.8 | 65.2 | 0.004 | ||
| Mortality 30-day – % | Men | 2.0 | 0.003 | 2.6 | 2.1 | 2.2 | 1.8 | 1.4 | 0.04 |
| Women | 2.8 | 3.8 | 3.6 | 2.6 | 1.9 | 1.6 | 0.01 | ||
| Mortality 1-year – % | Men | 5.2 | <0.001 | 7.1 | 5.7 | 4.9 | 4.9 | 3.9 | <0.001 |
| Women | 7.4 | 8.4 | 8.5 | 7.3 | 6.2 | 6.1 | 0.06 | ||
Catheterization = Cardiac Catheterization,
P-Value for unadjusted comparison accounting for facility clustering using GEE,
P-Value from trend test accounting for facility clustering using GEE
Women had lower unadjusted odds of receiving cardiac catheterization compared to men both within 2 days (OR 0.66; 95% CI, 0.57 – 0.75) and 30 days (OR 0.65; 95% CI, 0.52 – 0.80) of presentation and higher unadjusted odds of 30-day and 1-year mortality (OR 1.41; 95% CI, 1.13 – 1.76 and OR 1.46; 95% CI, 1.36 – 1.55). Table 3 summarizes the unadjusted and adjusted analyses that assume a linear relationship between neighborhood income quintile and the odds of receiving cardiac catheterization. For both sexes, when compared to patients from the highest-income areas, each decrease in neighborhood income quintile was associated with a lower unadjusted odds of receiving urgent but not emergency cardiac catheterization (Table 3).
Table 3.
Unadjusted and Adjusted Association of Decreasing Neighborhood Income Quintile on Outcomes by Sex
| Outcomes | Men N=9995 |
Women N= 4017 |
P-Value for Adjusted Interaction |
||
|---|---|---|---|---|---|
| Unadjusted OR [95% CI] |
Adjusted OR† [95% CI] |
Unadjusted OR [95% CI] |
Adjusted OR† [95% CI] |
||
| Catheterization* within 2 days | 0.92 [0.85 – 1.00] | 1.03 [1.02 – 1.05] | 0.91 [0.81 – 1.02] | 0.99 [0.93 – 1.06] | 0.21 |
| Catheterization* within 30 days | 0.96 [0.93 – 0.98] | 0.98 [0.95 – 1.00] | 0.93 [0.89 – 0.98] | 0.94 [0.89 – 0.98] | 0.21 |
| 30-Day Mortality | 1.14 [1.01 – 1.30] | 1.05 [0.95 – 1.15] | 1.27 [1.05 – 1.53] | 1.14 [1.01 – 1.28] | 0.003 |
| 1-Year Mortality | 1.16 [1.07 – 1.25] | 1.05 [0.98 – 1.14] | 1.11 [1.00 – 1.23] | 1.01 [0.93 – 1.09] | 0.02 |
Catheterization = Cardiac Catheterization,
Adjusted models included the following variables: age, sex, neighborhood median household income quintile, Interaction term for sex*neighborhood income quintile, distance from facility of presentation to facility with catheterization laboratory, Calendar year of presentation (2004–2011), ACS type, hypertension, dyslipidemia, diabetes, prior ACS, smoking, ex-smoking status, previous percutaneous coronary intervention, previous coronary artery bypass graft surgery, malignancy, congestive heart failure, peripheral vascular disease, cerebrovascular disease, chronic kidney disease, dialysis, chronic lung disease, liver and gastrointestinal disease
Adjusted Analysis of Cardiac Catheterization
In models adjusting for clinical covariates and nSES, women had significantly lower odds of receiving cardiac catheterization than men, either within 2 days (OR 0.80; 95% CI, 0.72 – 0.88) or 30 days or presentation (OR 0.74; 95% CI 0.63 – 0.87). In adjusted analyses of catheterization and mortality stratified by neighborhood income quintile and sex, men in the highest neighborhood income quintile (quintile 5) served as the reference group. Women in both the lowest and the highest neighborhood income quintiles were significantly less likely to receive cardiac catheterization within 2 days of presentation with ACS (Figure 1; Panel A). Men in the second neighborhood income quintile were significantly more likely than the highest neighborhood income quintile men to receive catheterization emergently within 2 days of presentation (Figure 1; Panel A). In contrast, women in each of the five area-income categories were significantly less likely to receive cardiac catheterization within 30 days of presentation compared to high neighborhood income men, with women in the lowest neighborhood income quintile particularly so (OR 0.58; 95% CI, 0.43 – 0.77) (Figure 1; Panel B). Among men, only those in the lowest neighborhood income quintile were significantly less likely to receive catheterization within 30-days of presentation (Figure 1; Panel B).
Figure 1.
The adjusted odds ratios of receiving cardiac catheterization within 2 and 30 days of presentation with an ACS by sex and neighborhood income quintile. A. Adjusted odds ratios of receiving a cardiac catheterization within 2 day of presentation with an ACS compared to men in the highest neighborhood income quintile. B. Adjusted odds ratios of receiving a cardiac catheterization within 30 days of presentation with an ACS compared to men in the highest neighborhood income quintile.
Table 3 summarizes the adjusted analyses that assume a linear relationship between neighborhood income quintile and the odds of receiving cardiac catheterization. We observed that for men there was a slight incremental increase in the odds of catheterization within 2 days of presentation with lower neighborhood income; with each decrease in neighborhood income quintile, the odds of receiving emergent catheterization increased by 3% (OR 1.03; 95% CI, 1.02 – 1.05) (Table 3). This relationship was not found among women, and there was no evidence of statistically significant effect modification by sex of the neighborhood income-catheterization relationship (p=0.21). For women, each incremental decrease in neighborhood income quintile was associated with a 6% (p=0.01) decrease in the odds of catheterization within 30-days of presentation (OR 0.94; 95% CI, 0.89 – 0.98) (Table 3). This association was not evident among men; however, the interaction term between sex and income was not statistically significant (p=0.21).
Adjusted Analysis of Mortality
In models adjusting for clinical covariates and nSES, when compared to men on average, women did not experience higher adjusted odds of 30-day or 1-year mortality (OR 0.92; 95% CI, 0.73 – 1.16, and OR 0.99; 95% CI, 0.92 – 1.05, respectively). In the adjusted analysis exploring the additive association of sex and nSES on mortality, only women in the highest neighborhood income quintile approached a significantly lower odds of 30-day mortality compared to high neighborhood income males (OR 0.81; 95% CI 0.65 – 1.00, p=0.05) (Figure 2; Panel A). Otherwise, there were no significant differences among the sex and neighborhood income groups for the adjusted odds of either 30-day or 1-year mortality (Figure 2).
Figure 2.
The adjusted odds ratios of all-cause mortality within 30 days and one year of presentation with an ACS by sex and neighborhood income quintile. A. Adjusted odds ratios of 30-day all-cause mortality after presentation with an ACS compared to men in the highest neighborhood income quintile. B. Adjusted odds ratios of all-cause mortality within 1 year of presentation with an ACS compared to men in the highest neighborhood income quintile.
In models assuming a linear relationship between neighborhood income and mortality (summarized in Table 3), each decrease in neighborhood income quintile was associated with a 14% (p=0.03) increase in the adjusted odds of 30-day mortality for women. In contrast, for men neighborhood income was not a significant predictor of 30-day mortality (Table 3). We used an interaction term to test for effect modification on the odds of 30-day mortality by nSES. This term was significant (p=0.003), thus confirming the association of nSES and 30-day mortality was modified by sex (Table 3).
Discussion
Our findings indicate significant relationships between neighborhood socioeconomic status and the receipt of cardiac catheterization and mortality after ACS for women but not men. We found that decreasing neighborhood income was associated with a lower a likelihood of receiving urgent catheterization within 30 days only for women. Additionally, we confirmed that women are less likely than men to undergo emergent or urgent cardiac catheterization in the setting of ACS even after adjusting for clinical characteristics, and that this was particularly apparent among women of lower neighborhood income. These findings were evident despite a universal health insurance system designed to eliminate cost barriers to medical care, especially in the setting of acute medical conditions such as ACS.
Furthermore, we found that sex modified the association between nSES and short-term mortality after presentation with ACS, whereby neighborhood income was predictive of 30-day mortality post-ACS for women but not for men. This differential association of nSES and short-term mortality in women appeared to be largely driven by a lower risk of 30-day mortality in women from high-income neighborhoods compared to men from these neighbourhoods.
Our study is novel in its exploration of the interplay between patient sex and nSES. Previous studies have shown women are less likely to receive invasive cardiac procedures than men, and women also experience higher short-term mortality and complications rates after an acute coronary syndrome.6,7,9,11,13,14,17,36 In addition, earlier studies showed that neighborhood income predicted both receipt of coronary angiography, wait times for angiography and mortality after acute myocardial infarction.23,37,38 However, more recent studies have indicated that these sex and SES-related disparities are mostly accounted for by age and important clinical comorbidities and might be improving over time.11,25,39,40 Similar to other studies, we found that on average women receive cardiac catheterization less often than men but that there were no significant differences between women and men in either short or long-term adjusted mortality.
Our study provides evidence that both men’s and women’s receipt of emergent cardiac catheterization (i.e., within 2 days of ACS) seemed largely unaffected by nSES. This is likely due to high adherence to standardized, emergency protocols in the setting of high-risk ACS.18 Differences in access to emergent catheterization between sexes may be due in part to previously described differences in symptom presentation or delays in seeking medical care among women.10,41–43 Alternatively, it is plausible that women presenting with lower-risk ACS (i.e., those with negative biomarkers) are appropriately treated without catheterization, and by extension, men presenting with ACS with low-risk features may be alternatively to subject to more overuse of cardiac catheterization and may explain some of the sex disparity observed in receipt of catheterization.7,20,44 For receipt of urgent coronary angiography in contrast, where more practice variation may exist, both men and women from low-income areas received urgent cardiac catheterization less often than men from high-income neighborhoods.19 This appeared to be particularly true for women from low-income neighborhoods and may represent the additive disadvantage of a gender bias and socioeconomic disparity in the receipt of medical care as opposed to a sex disparity with a biological basis.10
Our findings also provide evidence that female sex modifies the relationship between neighborhood income and short-term mortality. As opposed to previous studies have routinely shown the relationship between sex and short-term mortality among women is modified by age, our findings indicate this relationship between sex and mortality among women is modified by nSES11,14,42 We found a lower risk of short-term mortality among women from high-income neighborhoods compared to women of each subsequently lower quintile of neighborhood income. These mortality benefits for women from high-income areas may be driven by improvements over time in the receipt of evidence-based therapies and quality of care for women with ACS that are differentially being experienced by women of high vs. low nSES.11,45
Improved equity in adherence to evidence-based treatment for women in combination with the well-documented protective effects of estrogen and other physiologic differences may lead to lower short-term mortality for women after an ACS.46,47 Interestingly, lower mortality for women was not seen for women in lower income neighborhoods, thus indicating that these benefits are negated by the detrimental associations of low nSES status for women but not men. Recent literature describes increased clustering of traditional and non-traditional risk factors such as depression and chronic stress among low-income women in particular.28 The differential clustering of these important risk factors may indicate how women experience the detrimental associations of low nSES differently than men, and may also play an important role in modifying short-term mortality after ACS for women. Alternatively, lower nSES status may be predictive of how women relate to the healthcare system by progressively magnifying pre-existing gender biases within the healthcare system, thus leading to lower access to catheterization and worse outcomes for lower nSES women. We suspect that it is a combination of gender (i.e. psychosocial) and sex (i.e. biological) factors that lead to differences in cardiac care and outcomes between men and women in the setting of ACS. Future research is needed to disentangle these factors and their contributions to male/female disparities and the differential associations of nSES and sex with care and outcomes for ACS.
Our study has several limitations. First, we do not have information regarding physician or patient preferences around treatment decisions. Such information would shed light on the role of patient and provider preferences in clinical decision-making. Second, despite adjustment for several important clinical variables, there may be important unmeasured confounders or residual confounding of the relationship between sex, nSES, receipt of coronary angiography and post-ACS mortality. Third, although we found a strong neighborhood income gradient among women alone for the receipt of urgent cardiac catheterization, our power was limited to determine if the gradient was distinct from the experience of men. Fourth, we investigated the outcome of receiving cardiac catheterization, not the receipt of revascularization procedures that provide the therapeutic benefit after an ACS. We did this intentionally, recognizing that previous research has shown that women have higher rates of non-obstructive coronary artery disease in which revascularization may not be appropriate.48 Lastly, we remind readers that the use of neighborhood median household income is an approximation of socioeconomic status. While commonly used as a proxy for individual income, neighborhood income does not always reflect individual income.30,41–43 Reassuringly, however, previous studies have shown the prognostic relevance of this area level estimation of SES in patients presenting with myocardial infarction.19,23,30
These limitations notwithstanding, our study sheds light on the relationship between sex and nSES factors in cardiac care. The associations between neighborhood income and use of cardiac catheterization and mortality after ACS differ for men and women, with women seemingly more vulnerable to the detrimental associations of low area income. These findings occurred despite a universal healthcare system that does not have any inpatient user fees. These findings suggest that factors other than insurance status and/or ability to pay are at play. Care protocols designed to improve access to care and improve outcomes in women, especially low SES women, are required.
Supplementary Material
Acknowledgements
The authors would like to thank the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH) research committee for their support. Specifically, we gratefully acknowledge the contributions and support by Diane Galbraith. In addition, we would like to thank Dr. E. John Orav and Dr. E. Francis Cook at the Harvard School of Public Health for their guidance on the study design and statistical analyses. APPROACH was initially funded with a grant from the W. Garfield Weston Foundation. The ongoing operation of this project has been made possible by contributions from the Provincial Wide Services Committee of Alberta Health and Wellness and annual contributions from the Edmonton and Calgary zones of Alberta Health Services, as well as the Libin Cardiovascular Institute of Alberta and Mazankowski Alberta Heart Institute. We gratefully acknowledge the cardiac care personnel in the study hospitals for their diligence in data collection.
Sources of Funding
Dr. Fabreau received funding support from the University of Calgary, Department of Medicine Clinical Scholars program, the John A. Buchanan Chair in General Internal Medicine at the University of Calgary Faculty of Medicine, and the Ryoichi Sasakawa Fellowship Fund. Dr. Ghali is supported by a Senior Health Scholar award from Alberta Innovates Health Solutions. This work was conducted with support from Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health Award 8UL1TR000170-05 and financial contributions from Harvard University and its affiliated academic health care centers). The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic health care centers, or the National Institutes of Health.
Footnotes
Disclosures
None.
References
- 1.Manuel DG, Leung M, Nguyen K, Tanuseputro P, Johansen H. Burden of cardiovascular disease in Canada. Canadian Journal of Cardiology. 2003;19:997–1004. [PubMed] [Google Scholar]
- 2.Writing Group Members; Roger VL, Go AS, Lloyd-Jones DM, Benjamin EJ, Berry JD, Borden WB, Bravata DM, Dai S, Ford ES, Fox CS, Fullerton HJ, Gillespie C, Hailpern SM, Heit JA, Howard VJ, Kissela BM, Kittner SJ, Lackland DT, Lichtman JH, Lisabeth LD, Makuc DM, Marcus GM, Marelli A, Matchar DB, Moy CS, Mozaffarian D, Mussolino ME, Nichol G, Paynter NP, Soliman EZ, Sorlie PD, Sotoodehnia N, Turan TN, Virani SS, Wong ND, Woo D, Turner MB on behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee, On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart Disease and Stroke Statistics--2012 Update: A Report From the American Heart Association. Circulation. 2012;125:e2–e220. doi: 10.1161/CIR.0b013e31823ac046. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Healy B. The yentl syndrome. The New England Journal of Medicine. 1991;325:274–276. doi: 10.1056/NEJM199107253250408. [DOI] [PubMed] [Google Scholar]
- 4.Vaccarino V. Ischemic Heart Disease in Women: Many Questions, Few Facts. Circulation: Cardiovascular Quality and Outcomes. 2010;3:111–115. doi: 10.1161/CIRCOUTCOMES.109.925313. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Izadnegahdar M, Norris C, Kaul P, Pilote L, Humphries KH. Basis for Sex-Dependent Outcomes in Acute Coronary Syndrome. Canadian Journal of Cardiology. 2014:1–8. doi: 10.1016/j.cjca.2013.08.020. [DOI] [PubMed] [Google Scholar]
- 6.Ayanian JZ, Epstein AMA. Differences in the use of procedures between women and men hospitalized for coronary heart disease. The New England Journal of Medicine. 1991;325:221–225. doi: 10.1056/NEJM199107253250401. [DOI] [PubMed] [Google Scholar]
- 7.Kreatsoulas C, Sloane D, Pogue J, Velianou JL, Anand SS. Referrals in Acute Coronary Events for CARdiac catheterization: The RACE CAR trial. The Canadian journal of Cardiology. 2010;26:290–296. doi: 10.1016/s0828-282x(10)70436-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Blomkalns AL, Chen AY, Hochman JS, Peterson ED, Trynosky K, Diercks DB, Brogan GX, Jr, Boden WE, Roe MT, Ohman EM, Gibler WB, Newby LK. Gender disparities in the diagnosis and treatment of non–ST-segment elevation acute coronary syndromes. Journal of the American College of Cardiology. 2005;45:832–837. doi: 10.1016/j.jacc.2004.11.055. [DOI] [PubMed] [Google Scholar]
- 9.Rathore SS, Chen J, Wang Y, Radford MJ, Vaccarino V, Krumholz HM. Sex differences in cardiac catheterization: the role of physician gender. Journal of the American Medical Association. 2001;286:2849–2856. doi: 10.1001/jama.286.22.2849. [DOI] [PubMed] [Google Scholar]
- 10.Pelletier R, Humphries KH, Shimony A, Bacon SL, Lavoie KL, Rabi D, Karp I, Tsadok MA, Pilote L GENESIS-PRAXY Investigators. Sex-related differences in access to care among patients with premature acute coronary syndrome. CMAJ. 2014;186:497–504. doi: 10.1503/cmaj.131450. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Vaccarino V, Parsons L, Peterson ED, Rogers WJ, Kiefe CI, Canto J. Sex differences in mortality after acute myocardial infarction: changes from 1994 to 2006. Archives of Internal Medicine. 2009;169:1767–1774. doi: 10.1001/archinternmed.2009.332. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Abramson JL, Veledar E, Weintraub WS, Vaccarino V. Association between gender and In-Hospital mortality after percutaneous coronary intervention according to age. The American Journal of Cardiology. 2003;91:968–971. doi: 10.1016/s0002-9149(03)00114-0. [DOI] [PubMed] [Google Scholar]
- 13.Akhter N, Milford-Beland S, Roe MT, Piana RN, Kao J, Shroff A. Gender differences among patients with acute coronary syndromes undergoing percutaneous coronary intervention in the American College of Cardiology-National Cardiovascular Data Registry (ACC-NCDR) American Heart Journal. 2009;157:141–148. doi: 10.1016/j.ahj.2008.08.012. [DOI] [PubMed] [Google Scholar]
- 14.King KM, Ghali WA, Faris PD, Curtis MJ, Galbraith PD, Graham MM, Knudtson ML. Sex differences in outcomes after cardiac catheterization: effect modification by treatment strategy and time. Journal of the American Medical Association. 2004;291:1220–1225. doi: 10.1001/jama.291.10.1220. [DOI] [PubMed] [Google Scholar]
- 15.Bugiardini R, Yan AT, Yan RT, Fitchett D, Langer A, Manfrini O, Goodman SG on behalf of the Canadian Acute Coronary Syndrome Registry I and II Investigators. Factors influencing underutilization of evidence-based therapies in women. European Heart Journal. 2011;32:1337–1344. doi: 10.1093/eurheartj/ehr027. [DOI] [PubMed] [Google Scholar]
- 16.Opotowsky AR, McWilliams JM, Cannon CP. Gender Differences in Aspirin use Among Adults With Coronary Heart Disease in the United States. Journal of General Internal Medicine. 2007;22:55–61. doi: 10.1007/s11606-007-0116-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Milcent C, Dormont B, Durand-Zaleski I, Steg PG. Gender Differences in Hospital Mortality and Use of Percutaneous Coronary Intervention in Acute Myocardial Infarction: Microsimulation Analysis of the 1999 Nationwide French Hospitals Database. Circulation. 2007;115:833–839. doi: 10.1161/CIRCULATIONAHA.106.664979. [DOI] [PubMed] [Google Scholar]
- 18.O'Gara PT, Kushner FG, Ascheim DD, Casey DE, Chung MK, de Lemos JA, Ettinger SM, Fang JC, Fesmire FM, Franklin BA, Granger CB, Krumholz HM, Linderbaum JA, Morrow DA, Newby LK, Ornato JP, Ou N, Radford MJ, Tamis-Holland JE, Tommaso JE, Tracy CM, Woo YJ, Zhao DX. 2013 ACCF/AHA Guideline for the Management of ST-Elevation Myocardial Infarction: Executive Summary: A Report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2013;127:529–555. doi: 10.1161/CIR.0b013e3182742c84. [DOI] [PubMed] [Google Scholar]
- 19.2012 Writing Committee Members. Jneid H, Anderson JL, Wright RS, Adams CD, Bridges CR, Casey DE, Ettinger SM, Fesmire FM, Ganiats TG, Lincoff AM, Peterson ED, Philippides GJ, Theroux P, Wenger NK, Zidar JP, Anderson JL. 2012 ACCF/AHA Focused Update of the Guideline for the Management of Patients With Unstable Angina/Non-ST-Elevation Myocardial Infarction (Updating the 2007 Guideline and Replacing the 2011 Focused Update): A Report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation. 2012;126:875–910. doi: 10.1161/CIR.0b013e318256f1e0. [DOI] [PubMed] [Google Scholar]
- 20.O’Donoghue M, Boden WE, Braunwald E, Cannon CP, Clayton TC, de Winter RJ, Fox KA, Lagerqvist B, McCullough PA, Murphy SA. Early invasive vs conservative treatment strategies in women and men with unstable angina and non–ST-segment elevation myocardial infarction: a meta-analysis. Journal of the American Medical Association. 2008;300:71–80. doi: 10.1001/jama.300.1.71. [DOI] [PubMed] [Google Scholar]
- 21.Rahimi AR, Spertus JA, Reid KJ, Bernheim SM, Krumholz HM. Financial barriers to health care and outcomes after acute myocardial infarction. Journal of the American Medical Association. 2007;297:1063–1072. doi: 10.1001/jama.297.10.1063. [DOI] [PubMed] [Google Scholar]
- 22.Hanley GE, Morgan S, Reid RJ. Income-Related Inequity in Initiation of Evidence-Based Therapies Among Patients with Acute Myocardial Infarction. Journal of General Internal Medicine. 2011;26:1329–1335. doi: 10.1007/s11606-011-1799-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Chang W-C, Kaul P, Westerhout CM, Graham MM, Armstrong PW. Effects of Socioeconomic Status on Mortality after Acute Myocardial Infarction. American Journal of Medicine. 2007;120:33–39. doi: 10.1016/j.amjmed.2006.05.056. [DOI] [PubMed] [Google Scholar]
- 24.Salomaa V, Niemela M, Miettinen H, Ketonen M, Immonen-Raiha P, Koskinen S, Mahonen M, Lehto S, Vuorenmaa T, Palomaki P, Mustaniemi H, Kaarsalo E, Arstila M, Torppa J, Kuulasmaa K, Puska P, Pyorala K, Tuomilehto J. Relationship of Socioeconomic Status to the Incidence and Prehospital, 28-Day, and 1-Year Mortality Rates of Acute Coronary Events in the FINMONICA Myocardial Infarction Register Study. Circulation. 2000;101:1913–1918. doi: 10.1161/01.cir.101.16.1913. [DOI] [PubMed] [Google Scholar]
- 25.Alter DA, Chong A, Austin PC, Mustard C, Iron K, Williams JI, Morgan CD, Tu JV, Irvine J, Naylor CD SESAMI Study Group. Socioeconomic status and mortality after acute myocardial infarction. Annals of Internal Medicine. 2006;144:82–93. doi: 10.7326/0003-4819-144-2-200601170-00005. [DOI] [PubMed] [Google Scholar]
- 26.Williams C. Women in Canada: A Gender-based Statistical Report. [Accessed on March 1, 2014];Statistics Canada. 2010 :1–34. [Internet]. Available from: http://www.statcan.gc.ca/pub/89-503-x/2010001/article/11388-eng.htm. [Google Scholar]
- 27.Ruel E, Hauser RM. Explaining the Gender Wealth Gap. Demography. 2012;50:1155–1176. doi: 10.1007/s13524-012-0182-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Choi J, Daskalopoulou SS, Thanassoulis G, Karp I, Pelletier R, Behlouli H, Pilote L GENESIS-PRAXY Investigators. Sex- and gender-related risk factor burden in patients with premature acute coronary syndrome. The Canadian Journal of Cardiology. 2014;30:109–117. doi: 10.1016/j.cjca.2013.07.674. [DOI] [PubMed] [Google Scholar]
- 29.Ghali WAW, Knudtson MLM. Overview of the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease. On behalf of the APPROACH investigators. Canadian Journal of Cardiology. 2000;16:1225–1230. [PubMed] [Google Scholar]
- 30.Southern DA, McLaren L, Hawe P, Knudtson ML, Ghali WA APPROACH Investigators. Individual-level and neighborhood-level income measures: agreement and association with outcomes in a cardiac disease cohort. Medical Care. 2005;43:1116–1122. doi: 10.1097/01.mlr.0000182517.57235.6d. [DOI] [PubMed] [Google Scholar]
- 31.Bow CJD, Waters NM, Faris PD, Seidel JE, Galbraith PD, Knudtson ML, Ghali WA. Accuracy of city postal code coordinates as a proxy for location of residence. International Journal of Health Geographics. 2004;3:5. doi: 10.1186/1476-072X-3-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.World Health Organization. Gender, women and primary health care renewal: a discussion paper. [Accessed on March 19, 2014];World Health Organization. 2010 [Internet]. Available from: http://www.who.int/gender/documents/women_and_girls/9789241564038/en/
- 33.Google. Google Maps. [Accessed on March 1, 2014];2014 Available from: https://maps.google.com/ [Google Scholar]
- 34.Wallace DJ, Kahn JM, Angus DC, Martin-Gill C, Callaway CW, Rea TD, Chhatwal J, Kurland K, Seymour CW. Accuracy of Prehospital Transport Time Estimation. Academic Emergency Medicine. 2013;21:9–16. doi: 10.1111/acem.12289. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Southern DA, Norris CM, Quan H, Shrive FM, Galbraith PD, Humphries K, Gao M, Knudtson ML, Ghali WA. An administrative data merging solution for dealing with missing data in a clinical registry: adaptation from ICD-9 to ICD-10. BMC Medical Research Methodology. 2008;8:1. doi: 10.1186/1471-2288-8-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Blomkalns AL, Chen AY, Hochman JS, Peterson ED, Trynosky K, Diercks DB, Brogan GX, Jr, Boden WE, Roe MT, Ohman EM, Gibler WB, Newby LK. Gender disparities in the diagnosis and treatment of non–ST-segment elevation acute coronary syndromes. Journal of the American College of Cardiology. 2005;45:832–837. doi: 10.1016/j.jacc.2004.11.055. [DOI] [PubMed] [Google Scholar]
- 37.Alter DA, Naylor CD, Austin P, Tu JV. Effects of socioeconomic status on access to invasive cardiac procedures and on mortality after acute myocardial infarction. The New England Journal of Medicine. 1999;341:1359–1367. doi: 10.1056/NEJM199910283411806. [DOI] [PubMed] [Google Scholar]
- 38.Philbin EF, McCullough PA, DiSalvo TG, Dec GW, Jenkins PL, Weaver WD. Socioeconomic Status Is an Important Determinant of the Use of Invasive Procedures After Acute Myocardial Infarction in New York State. Circulation. 2000;102:107–115. doi: 10.1161/01.cir.102.suppl_3.iii-107. [DOI] [PubMed] [Google Scholar]
- 39.Pilote L, Tu JV, Humphries K, Behouli H, Belisle P, Austin PC, Joseph L. Socioeconomic status, access to health care, and outcomes after acute myocardial infarction in Canada's universal health care system. Medical Care. 2007;45:638–646. doi: 10.1097/MLR.0b013e3180536779. [DOI] [PubMed] [Google Scholar]
- 40.Fransoo RR, Martens PJ, Need to Know Team. Prior HJ, Burland E, Château D, Katz A. Age difference explains gender difference in cardiac intervention rates after acute myocardial infarction. Healthcare Policy. 2010;6:88–103. [PMC free article] [PubMed] [Google Scholar]
- 41.Khan NA, Daskalopoulou SS, Karp I, Eisenberg MJ, Pelletier R, Tsadok MA, Dasgupta K, Norris CM, Pilote L GENESIS-PRAXY Investigators. Sex Differences in Acute Coronary Syndrome Symptom Presentation in Young Patients. JAMA Internal Medicine. 2013;173:1863–1871. doi: 10.1001/jamainternmed.2013.10149. [DOI] [PubMed] [Google Scholar]
- 42.Canto JG, Rogers WJ, Goldberg RJ, Peterson ED, Wenger NK, Vaccarino V, Kiefe CI, Frederick PD, Sopko G, Zheng Z-J NRMI Investigators. Association of age and sex with myocardial infarction symptom presentation and in-hospital mortality. Journal of the American Medical Association. 2012;307:813–822. doi: 10.1001/jama.2012.199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Diercks DB, Owen KP, Kontos MC, Blomkalns A, Chen AY, Miller C, Wiviott S, Peterson ED. Gender differences in time to presentation for myocardial infarction before and after a national women's cardiovascular awareness campaign: A temporal analysis from the Can Rapid Risk Stratification of Unstable Angina Patients Suppress ADverse Outcomes with Early Implementation (CRUSADE) and the National Cardiovascular Data Registry Acute Coronary Treatment and Intervention Outcomes Network–Get with the Guidelines (NCDR ACTION Registry–GWTG) American Heart Journal. 2010;160:80–87. e3. doi: 10.1016/j.ahj.2010.04.017. [DOI] [PubMed] [Google Scholar]
- 44.Rathore SS, Wang Y, Radford MJ, Ordin DL, Krumholz HM. Sex differences in cardiac catheterization after acute myocardial infarction: the role of procedure appropriateness. Annals of Internal Medicine. 2002;137:487–493. doi: 10.7326/0003-4819-137-6-200209170-00008. [DOI] [PubMed] [Google Scholar]
- 45.Novack V, Cutlip DE, Jotkowitz A, Lieberman N, Porath A. Reduction in Sex-Based Mortality Difference with Implementation of New Cardiology Guidelines. American Journal of Medicine. 2008;121:597.e1–597.e8. doi: 10.1016/j.amjmed.2008.01.041. [DOI] [PubMed] [Google Scholar]
- 46.Deschamps AM, Murphy E, Sun J. Estrogen Receptor Activation and Cardioprotection in Ischemia Reperfusion Injury. Trends in Cardiovascular Medicine. 2010;20:73–78. doi: 10.1016/j.tcm.2010.05.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Xue B, Johnson AK, Hay M. Sex differences in angiotensin II- and aldosterone-induced hypertension: the central protective effects of estrogen. AJP: Regulatory, Integrative and Comparative Physiology. 2013;305:R459–R463. doi: 10.1152/ajpregu.00222.2013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Gulati M, Shaw LJ, Bairey Merz CN. Myocardial Ischemia in Women: Lessons From the NHLBI WISE Study. Clinical cardiology. 2012;35:141–148. doi: 10.1002/clc.21966. [DOI] [PMC free article] [PubMed] [Google Scholar]
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