Author + information
- Received February 9, 2015
- Revision received June 1, 2015
- Accepted June 2, 2015
- Published online August 11, 2015.
- Emily M. Bucholz, MD, PhD, MPH∗,
- Sharon-Lise T. Normand, PhD†,
- Yun Wang, PhD‡,
- Shuangge Ma, PhD§,
- Haiqun Lin, MD, PhD§ and
- Harlan M. Krumholz, MD, SM‡,‖,¶,#∗ ()
- ∗Yale School of Medicine and Yale School of Public Health, New Haven, Connecticut
- †Department of Health Care Policy, Harvard Medical School and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- ‡Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut
- §Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
- ‖Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut
- ¶Robert Wood Johnson Foundation Clinical Scholars Program, Yale University School of Medicine, New Haven, Connecticut
- #Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut
- ↵∗Reprint requests and correspondence:
Dr. Harlan M. Krumholz, Department of Internal Medicine, Yale University School of Medicine, 1 Church Street Suite 200, New Haven, Connecticut 06510.
Background Most studies of sex and race differences after acute myocardial infarction (AMI) have not taken into account differences in life expectancy in the general population. Years of potential life lost (YPLL) is a metric that takes into account the burden of disease and can be compared by sex and race.
Objectives This study sought to determine sex and race differences in long-term survival after AMI using life expectancy and YPLL to account for differences in population-based life expectancy.
Methods Using data from the Cooperative Cardiovascular Project, a prospective cohort study of Medicare beneficiaries hospitalized for AMI between 1994 and 1995 (N = 146,743), we calculated life expectancy and YPLL using Cox proportional hazards regression with extrapolation using exponential models.
Results Of the 146,743 patients with AMI, 48.1% were women and 6.4% were black; the average age was 75.9 years. Post-AMI life expectancy estimates were similar for men and women of the same race but lower for black patients than white patients. On average, women lost 10.5% (SE 0.3%) more of their expected life than men, and black patients lost 6.2% (SE 0.6%) more of their expected life than white patients. After adjustment, women still lost an average of 7.8% (0.3%) more of their expected life than men, but black race became associated with a survival advantage, suggesting that racial differences in YPLL were largely explained by differences in clinical presentation and treatment between black and white patients.
Conclusions Women and black patients lost more years of life after AMI, on average, than men and white patients, an effect that was not explained in women by clinical or treatment differences.
Eliminating sex and race differences in health requires an understanding of whether these differences are disease-specific or reflect differences in the broader population. Although numerous studies have examined sex and race differences in outcomes associated with particular conditions, most have not taken into account differences in life expectancy in the general population, leaving uncertainty as to whether the observed differences reflect broader differences in the general population or are specific to the condition. Differences in life expectancy by sex and race in the general population are essential to consider when investigating the sex and race differences in the burden of a particular condition.
Acute myocardial infarction (AMI) has received significant attention regarding sex and race differences, but uncertainty remains. Studies of sex differences in AMI have generally reported no differences in long-term survival between older men and women after risk adjustment (1–7), but these analyses have not considered women’s longer life expectancy in the general population (8). Similarly, studies of racial differences among patients with AMI have consistently reported poorer long-term survival for black patients compared with white patients (9–11), but it is unclear whether these differences in mortality are disease-specific or simply reflect the shorter life expectancy of blacks in the general population (8).
Understanding the distinction between disease-specific and broader health differences is critical for targeting efforts to reduce sex and racial differences among patients with AMI. If the observed differences are specific to patients with AMI, then efforts should target factors related to the AMI such as sex and race differences in presentation and care. Alternatively, if the observed differences are due to differences in life expectancy in the general population, then efforts should target factors contributing to health disparities in the general population, such as socioeconomic status or access to care.
Years of potential life lost (YPLL) can incorporate information about the general population experience when investigating the burden of a particular condition. YPLL measure the difference in life expectancy between patients with a particular condition and persons with similar characteristics in the general population. Thus, YPLL provide a direct assessment of disease-related mortality and allow us to separate sex and race differences in post-AMI mortality from background sex and race differences in the general population (12). To date, no large national studies have examined YPLL from AMI, because such analyses require massive studies of patients with AMI and the general population, each with long-term follow-up. Although a few studies have accounted for sex or race differences in population-based mortality using methods other than YPLL (13–16), their results have been limited by small sample sizes and short follow-up. To investigate disease-specific sex and race differences after AMI, we used data from the Cooperative Cardiovascular Project (CCP) to calculate life expectancy and YPLL after AMI by men and women and blacks and whites. Implemented by the Health Care Financing Administration (now the Centers for Medicare & Medicaid Services) in the mid-1990s, the CCP contains rich, detailed clinical data and now has more than 17 years of follow-up on Medicare beneficiaries.
The CCP was a nationwide quality improvement project conducted in the mid-1990s, designed to evaluate and improve the care of AMI patients in the United States (17,18). In brief, the CCP is a prospective cohort study that includes all fee-for-service Medicare beneficiaries discharged from acute-care nongovernmental U.S. hospitals, with the principal discharge diagnosis of AMI (International Classification of Diseases-Ninth Revision-Clinical Modification, code 410). Patients were identified between January 1994 and February 1996 using hospital bills (UB-92 claims data) in the Medicare National Claims History file. Patient records were abstracted for detailed clinical information, including demographics, medical history, presentation, laboratory, and electrocardiographic data, in-hospital events, and treatment. AMI readmissions (code 410.x2) were excluded, resulting in 234,771 admissions.
We limited our sample to patients between ages 65 and 90 years with confirmed AMI by standardized criteria. Confirmed AMI was defined as an elevation of creatine kinase-MB (>5% of total creatine kinase), an elevation of lactate dehydrogenase level >1.5 times the upper limit of normal with isoenzyme reversal, or the presence of 2 of the following: chest pain before admission, a 2-fold elevation in total creatine kinase, and electrocardiographic evidence of AMI (ST-segment elevation or new pathological Q waves). Patients <65 years of age (n = 17,593), >90 years of age (n = 9,985), and those without clinically confirmed AMI (n = 31,186) were excluded. For patients hospitalized more than once during the study period, we excluded admissions after the first admission (n = 23,773). We also excluded patients who were hospitalized outside the 50 states (n = 1,763) and patients whose records could not be linked to the Medicare Denominator files to ascertain vital status (n = 2,195). Finally, we calculated life expectancy for black and white patients only, because so few patients were classified as other races (n = 9,010). Our final sample size included 146,743 patients. The Yale University Institutional Review Board approved this study.
We linked the CCP to Medicare Denominator files from 1994 to 2012 to obtain data on 17-year survival from the time of hospital admission. Denominator files contain demographic and enrollment information on all Medicare fee-for-service and Medicare Advantage beneficiaries in a given year, including age, sex, race, and date of death. Only Medicare fee-for-service patients were used.
Patient characteristics collected during the index admission were compared between men and women using chi-square tests and Student t tests. Age-, sex-, and race-specific estimates of life expectancy were calculated using a 3-step process. First, we fit a Cox proportional hazards model that included covariates age, sex, race, and their pairwise interactions. We chose a semiparametric approach, because it provided better fit to the data using the Akaike Information Criterion and likelihood ratio statistics compared with parametric models such as the Weibull or Gompertz. Proportional hazards assumptions were checked using Schoenfeld residuals, examined graphically, and tested formally. Second, we plotted the 17-year expected survival curves from the Cox models for each age, sex, and race combination and then extrapolated the curves to age 100 using exponential models. We chose an exponential model because we lacked information on the shape of the hazard function beyond 17 years and thus opted for a model with a constant hazard that does not make assumptions about changes to the hazard function over time. The constant hazard for the exponential model was specified as the average hazard over the last 2 years of available follow-up. For example, to calculate life expectancy for a 65-year-old white man, we plotted the survival curve for these specific covariate values over 17 years of follow-up and then extrapolated the survival curve using an exponential model over an additional 18 years. Third, mean life expectancy estimates were calculated by adding the areas under the Cox and exponential survival functions. The 95% confidence intervals (CIs) for the mean were calculated using the same process for the upper and lower confidence bounds of the expected survival curves.
To estimate YPLL, we subtracted observed patient survival from age-, sex-, and race-specific estimates of life expectancy for the overall Medicare population. Life expectancy estimates for the overall Medicare population in 1994 and 1995 were calculated using the same methods described in the preceding text with data from the Medicare Denominator files. For patients in the CCP who survived the 17-year follow-up, we used a multiple imputation approach with 10 repetitions to estimate expected survival. The distribution of expected survival was calculated by adding the area under the exponential portion of the survival curve to the observed 17-year survival for each age, sex, and race combination. Survivors were then assigned a random survival time from this distribution to create a complete dataset. Because the observed differences in YPLL could be influenced by sex and race differences in life expectancy in the general population, we standardized YPLL by calculating the percentage of years of potential life lost (or gained) against life expectancy in the Medicare population.
To evaluate whether differences in cardiovascular risk factors, clinical presentation, or treatment might explain the observed sex and racial differences in YPLL, we used multivariable linear regression with multiple imputations to sequentially adjust for patient medical history (history of congestive heart failure, diabetes mellitus, hypertension, coronary artery disease, and smoking), clinical presentation (anterior AMI, ST-segment elevation AMI, cardiac arrest, Killip class, and renal insufficiency), and treatment (revascularization procedures within 30 days, fibrinolytic therapy during hospitalization, aspirin on arrival, beta-blockers at discharge, and eligibility for core measures). Covariates were selected using a combination of clinical judgment, existing risk models, and significance testing. Patients with missing data on revascularization procedures were included in the model using dummy variables to denote missing data. We modeled the percentage of YPLL to expected survival rather than absolute YPLL because these values were standardized against expected population life expectancy and thus more appropriately reflected mortality related to the AMI versus competing causes. We evaluated model assumptions using studentized residuals assessed both graphically and formally. All statistical analyses were performed using SAS version 9.3 (SAS Institute, Cary, North Carolina).
Of the 146,743 patients with AMI in our cohort, 48.1% were women and 6.4% were black (Table 1). The mean age ± SD at the time of AMI hospitalization was 74.8 ± 6.5 years for white men, 77.2 ± 6.8 years for white women, 74.0 ± 6.4 years for black men, and 75.4 ± 6.7 years for black women. Women and black patients had a greater prevalence of diabetes mellitus, hypertension, and heart failure compared with white men. At the time of hospital presentation, more women were classified as Killip class III or IV than were men, and black patients were more likely to demonstrate signs of renal insufficiency and bleeding. Overall, men and white patients were more likely to undergo revascularization procedures and to receive fibrinolytic therapy than women and black patients, respectively.
The survival rate after 17 years of follow-up was 8.3% for white men, 6.4% for white women, 5.4% for black men, and 5.8% for black women (7.3% overall). Men and women of the same race had similar life expectancy after AMI at all ages; only minimal differences by sex were observed in the youngest and oldest ages (Figure 1A). By contrast, black patients had lower life expectancies after AMI than white patients at younger ages, but comparable life expectancies at older ages.
Compared with AMI patients, more patients in the general Medicare population were female (58.5% vs. 48.1%) and black (8.2% vs. 6.4%). Figure 1B shows the life expectancy estimates for the general Medicare population by age, sex, and race. Compared with the life expectancy estimates shown in Figure 1A, patients in the general Medicare population lived significantly longer than patients with AMI of the same age, sex, and race. In the general population, women had longer life expectancies than men of the same race at all ages. Conversely, black patients had lower life expectancies at younger ages than white patients of the same sex but longer life expectancies in the oldest ages.
Mean YPLL by sex and race are presented in Figure 2. On average, women lost 1.86 (95% CI: 1.74 to 1.99) more years of life than men across all ages, and black patients lost 0.86 (95% CI: 0.12 to 0.23) more years of life than white patients. However, the magnitude of these differences varied by age and across different combinations of sexes and races. Figure 3 shows the absolute number of YPLL by age, sex, and race. Across all ages, women lost more years of potential life after AMI than men did, although the difference was most pronounced among patients in younger patients. For example, 65-year-old white women lost an average of 9.99 (95% CI: 9.83 to 10.16) years after AMI compared with only 5.11 (95% CI: 4.97 to 5.26) years in white men. Differences in life-years lost by race were less pronounced. Whereas 65-year-old white men lost an average of 5.11 (95% CI: 4.97 to 52.6) years, black men lost 5.17 (95% CI: 4.80 to 5.53) years.
The percentages of YPLL are presented in Figure 4. Among younger patients, black women lost the greatest percentage of YPLL after AMI, followed by white women then black men (p < 0.001 for differences across groups). For example, among patients aged 65 at the time of AMI, black women lost 54.4% (SE 0.9%) of their potential life after AMI, whereas white men lost only 29.1% (SE 0.4%) of their potential life. Sex and racial differences in YPLL percentages were greatest among younger ages but became diminished in the oldest patients (p = 0.25 and p = 0.27 for sex and race, respectively).
Both female sex and black race were highly predictive of increased YPLL in unadjusted analyses (Tables 2 and 3⇓). On average, men lost 41.8% of their remaining life after AMI, whereas women lost 10.5% (SE 0.3%) more of their remaining life than men (52.3% total). Similarly, white patients lost an average of 46.4% of their remaining life after AMI, whereas black patients lost 6.2% (SE 0.6%) more of their remaining life than white patients (52.6% total). After adjustment for demographics, medical history, clinical presentation, and treatment, women still lost an average of 7.8% (SE 0.3%) more of their remaining life than men; however, the association between black race and percentage of YPLL switched directions, with black patients losing 3.5% (SE 0.5%) less of their remaining life than white patients. The greatest attenuation in the effect of black race occurred after adjustment for diabetes mellitus, congestive heart failure, clinical presentation, and receipt of revascularization therapies. Additional information on survival rates by age, sex, and race, the expected survival curves, and life expectancy, and YPLL estimates are provided in the Online Appendix.
In this study, we found large differences in life expectancy and YPLL between sexes and races, with younger women and black patients having the largest YPLL (Central Illustration). Men and women of the same race had similar post-AMI life expectancies; however, younger women lost significantly more years of life after AMI compared with men of the same age. Per 1,000 patients hospitalized for AMI, white women lost 1,808 more years than white men, and black women lost 2,451 more years than black men; these differences were more pronounced in younger patients.
By adopting a population perspective, our findings shed new light on sex differences in survival after AMI in elderly patients. Previous studies have invariably restricted their analyses to patients with AMI and have not considered the entire population experience. As a result, they have generally reported higher crude mortality rates for women after AMI that become attenuated after adjustment for age and clinical factors (7). Like other studies, our study found similar life expectancies for men and women after AMI. However, after accounting for differences in expected survival, women lost significantly more years of life than men and remained at a significant survival disadvantage even after multivariable adjustment. For example, we estimated that 65-year-old white men and women are estimated to lose 5.1 and 10.0 years of life after AMI. Sixty-five-year-old white men are expected to live another 17.6 years and white women another 21.7 years, this translates into a 29% reduction in remaining life for men and a 41% reduction for women. Thus, 65-year-old white women are losing 4.9 more years of life, or 12% more, of their remaining life than men. Thus, strategies to avert AMI in women may actually produce more benefit than in men.
To our knowledge, only 3 studies have accounted for expected mortality when comparing sex differences in survival after AMI (13–15). Using Cox proportional hazards models with time-dependent covariates, Vaccarino et al. (15) found that AMI was associated with a greater risk of 10-year mortality in women and significantly narrowed women’s typical survival advantage over men. Similarly, Peeters et al. (14) conducted a life table analysis of the Framingham Heart Study cohort to estimate life years lost among 60-year-old men and women with a history of AMI. As in our study, they reported larger reductions in life expectancy for women than men with a history of AMI (13 vs. 9 years, respectively). By contrast, Howland et al. (13) found no difference in 5-year relative survival between men and women after standardizing observed survival against national rates. Discrepancies in study findings are likely attributable to differences in study populations, methods, and length of follow-up.
Although we would expect women to live longer than men after AMI because of their life expectancy in the general population, AMI appears to act as an equalizer by negating women’s survival advantage. These sex differences in YPLL may be due to intrinsic biological and psychosocial factors, or disparities in care during or after the index hospitalization. Indeed, the magnitude of the difference in YPLL between men and women decreased slightly after adjustment for in-hospital treatment. Previous studies have found differences in rates of angiography, primary care, and cardiology follow-up in the year following AMI between men and women (19). These findings suggest that part of the sex difference in YPLL may be attributable to differences in the quality of care received. Although we can speculate as to how much of this difference is due to biological differences between men and women versus disparities in care, it is likely some combination of both. Additional research is needed to disentangle these effects.
Black patients generally had lower life expectancies post-AMI than white patients, which persisted after accounting for racial differences in population-based life expectancy. On average, black men lost 0.3 more years of life than white men, and black women lost 1.0 more years of life than white women. In relative percentages, this equates to an additional 5% more time lost by black men and women compared with white patients, which suggests that the burden of AMI is higher in black than in white patients. Racial differences in disease burden, however, were largely explained by differences in comorbidities and treatment utilization between black and white patients; adjustment for these factors attenuated racial differences in post-AMI YPLL.
Our results are consistent with, but also extend, the previous literature on racial differences in outcomes after AMI. Most studies of racial differences after AMI have reported comparable or lower mortality for black patients in the short term (20–23), but higher mortality over the long term as compared with white patients (9–11). Many studies have hypothesized that racial differences in long-term mortality are due to a higher prevalence of comorbid conditions and lower utilization of invasive therapies in black patients (9,22,24–27). Accordingly, we found that black patients had a higher prevalence of diabetes mellitus, hypertension, and heart failure, and they were significantly less likely to receive interventional procedures within 30 days compared with white patients (21.4% vs. 30.7%; p < 0.0001).
Implications of findings
The distinction between disease-specific differences and differences in the broader population is fundamental to understanding how the burden of AMI differs by sex and race and effectively targeting research and interventions. Our observation that women and black patients with AMI are losing more years of life after AMI places a premium on secondary prevention in these groups and underscores the importance of national efforts to ensure equitable delivery of care. Because racial differences in YPLL after AMI were largely explained by the poorer clinical presentation and lower treatment rates in black patients, efforts to reduce racial differences should target risk factor management and disparities in cardiac care. By contrast, sex differences in YPLL were not attenuated after multivariable adjustment, suggesting the need for additional research to understand this difference, which may be explained by either biological and psychosocial differences or other disparities in care. Strategies that warrant investigation include reducing the higher risk factor burden in women and improving long-term management of heart disease.
Additionally, by accounting for population-based life expectancy in our analyses, we demonstrated relationships between sex, race, and post-AMI survival that could not be detected using traditional mortality estimates. Although most datasets lack the representativeness and length of follow-up afforded by the CCP, several other techniques for adjusting for population differences in life expectancy have been described, which may be feasible for studies with shorter follow-up or smaller sample sizes. Such techniques include “relative survival,” life table methods, parametric survival methods, and Monte Carlo simulations (12,28–33). Regardless of the method selected, studies comparing disease-related survival between patients with different life expectancies should consider the overall population experience in their analyses.
We recognize that our analysis has several limitations. First, black patients represented only 6.4% of the cohort, which resulted in small numbers of patients in the older age-, sex-, and race-specific strata. We modeled the cohort using semiparametric techniques to avoid stratum-specific estimation. Nonetheless, the small sample sizes in some strata may still have limited the predictive power of our models. Second, approximately 10% of patients in the CCP were still alive after 17 years of follow-up, which required extrapolation of the expected survival curves in order to calculate life expectancy. It is possible that using an exponential model may have led to slightly biased estimates. Third, we lacked medical history information for patients in the Medicare Denominator files, and thus were unable to estimate life expectancy in an “AMI-free” population. Using age-, sex-, and race-specific AMI incidence from the Atherosclerosis Risk in Communities Surveillance Study, we estimate that the prevalence of AMI in the general Medicare population was 14% in white men, 9% in white women, 21% in black men, and 14% in black women (34). Because the average age of coronary heart disease (CHD) onset in men precedes that in women, and black patients have a higher incidence of CHD than white patients at all ages, the observed sex differences in life expectancy in the general Medicare population may be partly attributable to the higher prevalence of CHD in men, which may in turn affect the magnitude of sex and race differences in YPLL we calculated. Fourth, the YPLL reported in this study may be attributable to factors other than AMI. Because patients with AMI have a greater burden of cardiovascular risk factors than patients in the general population, the higher long-term mortality in patients with AMI may be due, in part, to other comorbidities. Similarly, sex and race differences in YPLL after AMI may reflect differences in the burden or management of other conditions that are more common in patients with AMI such as diabetes and heart failure. Although it was not possible to adjust for these factors when calculating life expectancy estimates for the general population, we addressed this issue, in part, by adjusting for sex and race differences in the prevalence of these risk factors and comorbidities at baseline. However, it is still possible that the adjusted differences in YPLL between men and women are attributable to sex differences in the care or outcomes of other AMI-related conditions. Finally, because the quality of care for patients with AMI has improved since the mid-1990s and patients are living longer today, the life expectancy estimates reported in this paper may not accurately reflect those of patients today. Additionally, there have been several national efforts over the last 2 decades to increase awareness of heart disease in women and to reduce racial differences in health outcomes. Nevertheless, data from nationally representative cohorts suggest that although sex and race differences in mortality after AMI have declined over time, there remains a persistent difference (7,35). Although these data would suggest that race and sex differences today are likely smaller than those found in CCP, life expectancy estimates in the general population have also increased by over a year since the mid-1990s (36). Thus, it is difficult to speculate on how the magnitude of these differences has changed over time when standardized again the general population. These limitations are inherent to any study that involved long follow-up.
Although these analyses have their limitations, this study has several strengths that allow us to disentangle disease-specific differences from those in the broader population over the lifespan. Calculation of life expectancy requires complete follow-up over many years, which contemporary datasets currently lack. Although clinical advances and performance improvement efforts have improved the care for patients with AMI since the mid-1990s, life expectancy calculations are necessary to understand how sex and race differences persist and evolve over time, and are only possible with long-term follow-up. Additionally, thorough adjustment for differences in patient and hospital characteristics between patients requires detailed clinical information, which only a dataset like CCP can offer.
In conclusion, we found that after adjusting for differences in population-based life expectancy, women and black patients were at significantly higher risk of losing more years of life after AMI. Whereas much of the racial difference in years of potential life lost could be explained by differences in clinical presentation and treatment between black and white patients, this was not true for the observed sex differences.
COMPETENCY IN MEDICAL KNOWLEDGE: Women and black patients lose more years of life, on average, than men and white patients, respectively, after AMI. Racial differences are explained by higher comorbidity and lower treatment rates in black patients.
TRANSLATIONAL OUTLOOK: Additional research is needed to understand why women face a long-term survival disadvantage after AMI compared with men and to identify targets for secondary prevention linked to survival.
The authors acknowledge the assistance of Qualidigm and the Centers for Medicare & Medicaid Services (CMS) in providing data, which made this research possible. The content of this publication does not reflect the views of Qualidigm or CMS, nor does mention of organizations imply endorsement by the U.S. Government. The authors assume full responsibility for the accuracy and completeness of the ideas presented.
For a supplemental figure and tables, please see the online version of this article.
Dr. Bucholz is supported by F30 Training grant F30HL120498-01A1 from the National Heart, Lung, and Blood Institute and by NIGMS Medical Scientist Training Program grant T32GM07205. Dr. Krumholz is supported by grant U01 HL105270-05 (Center for Cardiovascular Outcomes Research at Yale University) from the National Heart, Lung, and Blood Institute. Dr. Normand is a member of the Board of Directors of Frontier Science and Technology. Dr. Krumholz has received research agreements from Medtronic, Inc. and Johnson and Johnson through Yale University for the purpose of disseminating clinical trials; works under contract with the Centers for Medicare and Medicaid Services to develop and maintain performance measures; and chairs the Cardiac Scientific Advisory Board for United Health. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Abbreviations and Acronyms
- acute myocardial infarction
- Cooperative Cardiovascular Project
- coronary heart disease
- confidence interval
- years of potential life lost
- Received February 9, 2015.
- Revision received June 1, 2015.
- Accepted June 2, 2015.
- American College of Cardiology Foundation
- Benderly M.,
- Behar S.,
- Reicher-Reiss H.,
- Boyko V.,
- Goldbourt U.,
- SPRINT Study Group
- Goldberg R.J.,
- Gorak E.J.,
- Yarzebski J.,
- et al.
- He J.,
- Klag M.J.,
- Whelton P.K.,
- et al.
- Bucholz E.M.,
- Butala N.M.,
- Rathore S.S.,
- et al.
- Arias E.
- Mehta R.H.,
- Marks D.,
- Califf R.M.,
- et al.
- Peeters A.,
- Mamun A.A.,
- Willekens F.,
- Bonneux L.
- Vaccarino V.,
- Berkman L.F.,
- Krumholz H.M.
- Ramunno L.D.,
- Dodds T.A.,
- Traven N.D.
- Alter D.A.,
- Naylor C.D.,
- Austin P.C.,
- Tu J.V.
- Tofler G.H.,
- Stone P.H.,
- Muller J.E.,
- et al.
- Haybittle J.L.
- Go A.S.,
- Mozaffarian D.,
- Roger V.L.,
- et al.
- ↵Centers for Disease Control and Prevention. Life expectancy at birth, at 65 years of age, and at 75 years of age, by race and sex: United States, selected years 1900–2007. Available at: http://www.cdc.gov/nchs/data/hus/2010/022.pdf. Accessed April 11, 2015.