Abstract
Black individuals have higher incident fatal coronary heart disease (CHD) than White counterparts. Racial differences in out-of-hospital fatal CHD could explain the excess risk in fatal CHD among Black persons. We examined racial disparities in in- and out-of-hospital fatal CHD among people with no previous history of CHD, and whether socioeconomic status might play a role in this association. We used data from the Atherosclerosis Risk in Communities study, including 4095 Black and 10884 White participants, followed between 1987–89 until 2017. Race was self-reported. We examined racial differences in in- and out-of-hospital fatal CHD with hierarchical proportional hazard models. We then examined the role of income in these associations using Cox marginal structural models for a mediation analysis. The incidence of out-of-hospital and in-hospital fatal CHD was 1.3 and 2.2 in Black participants, and 1.0 and 1.1 in White participants per 1,000 person-years, respectively. The sex- and age-adjusted hazard ratios comparing out-of-hospital and in-hospital incident fatal CHD in Black versus White participants were 1.65 (1.32–2.07) and 2.37 (1.96–2.86) respectively. The income-controlled direct effects of race in Black vs. White participants attenuated to 1.33 (1.01–1.74) for fatal out-of-hospital and to 2.03 (1.61–2.55) for fatal in-hospital CHD in Cox marginal structural models. In conclusion, higher rates of fatal in-hospital CHD in Black participants vs. White counterparts likely drive the overall racial differences in fatal CHD. Income largely explained racial differences in both fatal out-of-hospital CHD and fatal in-hospital CHD.
Keywords: racial disparities, out-of-hospital deaths, coronary heart disease
Introduction
While the incidence and mortality of coronary heart disease (CHD) have been declining over the past several decades in the United States1–3, Black individuals continue to have higher prevalence of CHD, and higher hospitalization rates and mortality from CHD than White individuals4–10. However, these disparities do not seem to persist when considering non-fatal CHD events8,11. Studies from large population studies have reported no difference in total CHD incidence among Blacks versus White individuals8,11. However, in the same populations, Black men showed a higher incidence of fatal CHD and case-fatality than White men8,11. These findings could be driven by a higher rate of out-of-hospital CHD deaths in Black individuals, perhaps because of a lower access to healthcare, if a larger proportion of fatal CHD events occur before reaching the hospital in Black individuals compared with White counterparts. Existing studies of CHD mortality differences by race have rarely considered racial differences in fatal out-of-hospital CHD. Furthermore, most previous studies were conducted among Medicare beneficiaries ≥65 years of age, which could mask race-related disparities since Black individuals tend to develop CHD and die from it earlier in life than White individuals8,12–19. Also, income was highly associated with sudden cardiac death in previous studies perhaps through its relationship with healthcare access, health education, and lifestyle behaviors20,21. In the Atherosclerosis Risk in Communities (ARIC) study, we examined racial differences in the rates of out-of-hospital and in-hospital (post-admission) incidence of fatal CHD among US adults free of CHD at baseline. We explored the role of income in these associations in our models while we adjusted for cardiovascular risk factors.
Methods
The ARIC study is a prospective epidemiologic study conducted in 4 US communities (Washington County, MD; Forsyth County, NC; Jackson, MS; and selected Minneapolis suburbs, MN)22. Each ARIC field center randomly selected and recruited a cohort of approximately 4000 individuals aged 45–64 years from a defined community. Since very few Non-White and Non-Black participants participated in ARIC (n=48), we excluded them from the analysis. After excluding individuals who had prevalent CHD at baseline (n=766), our analysis included 14979 ARIC participants.
Participants received an extensive in-person evaluation, where sociodemographic and cardiovascular data were collected. Participants were reexamined in person every 3 years for the first 9 years (1990–92, 1993–95, 1996–98), with additional exams in 2011–13, 2016–17, and 2018–19. Also, participants were contacted by phone yearly (biannually since 2012) to update contact information and assess their health status. At visit 1 (baseline, 1987–1989), trained interviewers administered a questionnaire to collect data on demographic characteristics, medical history, and cardiovascular risk factors. Information on household income and years of education was also collected. Follow-up is ongoing in ARIC, however, in this analysis we ended the follow-up in 2017 since the adjudicated endpoint data for the Jackson site is currently available through 12/31/2017. Incident CHD events which occurred between the start of the data collection (1987–89) up to 12/31/2017 were included in the analysis. Procedures applied at all study centers were approved by each institutional review board, and informed consent was obtained from all participants.
Self-reported race at visit 1 was the exposure variable, which was classified as “Black participants” and “White participants”.
In ARIC, CHD events were ascertained by surveying discharge lists from local hospitals and death certificates from state vital statistics and follow-up calls identifying hospitalizations and deaths during the previous year. We followed the standard definitions of events in ARIC to define a CHD event. A participant in the ARIC cohort was considered to have a CHD event if they had a definite or probable acute myocardial infarction (AMI) or a fatal CHD during the follow-up. The definition of AMI required the presence of at least one of the following: 1) evolving diagnostic ECG pattern; (2) diagnostic ECG pattern and abnormal biomarkers; (3) cardiac pain and abnormal biomarkers; (4) cardiac pain and equivocal biomarkers with evolving ST-segment/T-wave pattern or diagnostic ECG pattern; or (5) abnormal biomarkers with evolving ST-segment/T-wave pattern. Fatal out-of-hospital CHD included deaths of participants who died at home or in other undefined places, or “deaths on arrival” to the hospital or deaths occurring in nursing homes. Fatal in-hospital CHD included deaths that occurred in hospitals. In ARIC, fatal out-of-hospital CHD events were ascertained and adjudicated after a special investigation. Additional information was sought from the next of kin and other informants, certifying doctors and family physicians, and coroners or medical examiners for out-of-hospital deaths. The next of kin was contacted for an interview, and information was sought from physicians by sending the Physician Questionnaire. Information on all out-of-hospital deaths was reviewed by 2 members of the expert committee of ARIC for event adjudication, in order to classify the event as “definite fatal CHD” using established criteria. These criteria remained the same during the follow-up. More information on the event classification is given in the ARIC Study surveillance manual22.
Income was included to our main models in 5 groups: < $16000, $16000 to $25000, $25000 to $35000, $35000 to $50000, ≥ $50000. Cardiovascular risk factors included body mass index (BMI), prevalent hypertension, prevalent diabetes, smoking status, and total cholesterol levels measured at visit 1. BMI was calculated as weight (in kilograms) divided by the square of height (meters) and was classified as “< 30.0” and “≥ 30.0”. Prevalent hypertension was defined as a systolic blood pressure of at least 140 mmHg or a diastolic blood pressure of at least 90 mmHg or use of hypertension medication. Blood pressure was measured by a certified technician using a random-zero sphygmomanometer after 5 minutes of rest and the average of the last 2 of the 3 seated measurements was used. Prevalent diabetes was defined as a fasting glucose level of at least 126 mg/dL, or a casual blood glucose level of at least ≥ 200 mg/dL, or a self-reported diagnosis of diabetes by a physician or use of antidiabetic medications. Fasting glucose levels were measured by the modified hexokinase/glucose-6 phosphate dehydrogenase method. Fasting plasma total cholesterol concentration was assessed by enzymatic procedures and was classified as “< 200 mg/dl” or “≥ 200 mg/dl”. Smoking status was classified as “current”, “former” and “never” smoker.
First, we tabulated the distributions of baseline sociodemographic factors and cardiovascular risk factors by race. Next, we computed incidence per 1000 person-years and 95 % confidence intervals (CI) for fatal, non-fatal, and total CHD by race. For fatal CHD, we examined out-of-hospital and in-hospital CHD deaths separately.
We constructed age- and sex-adjusted Cox proportional hazard models (Model 1) to compare fatal out-of-hospital and fatal in-hospital CHD, non-fatal CHD, and total incident CHD between Black and White participants. While constructing Cox proportional hazard models for fatal CHDs, we used a time to event analysis approach. In this analysis for fatal CHD, individuals who had prior non-fatal CHD events during the entire follow-up were not censored but individuals who died of other non-CHD causes were censored. In parallel to our main hypothesis, that income, as a socioeconomic indicator, helps explain racial disparities in outcomes and because differences in income could drive differences in cardiovascular risk factors, income was considered a more proximal exposure than cardiovascular risk factors and was included first in the second model (Model 2). We then added cardiovascular risk factors in fully-adjusted Model 3 to examine the mitigation of the remaining excess risk in Black participants vs. White participants. As a secondary analysis, we created models where cardiovascular risk factors were included first in Model 2, without income, to compare the results with the initial modelling approach.
We used logistic regression to examine racial differences in case-fatality among those hospitalized. We tested multiplicative race and sex interactions using Cox proportional hazard models adjusted for age. These models included in the interaction term ‘sex*race’ as well as variables age, sex and race. Then, considering the results of the interaction testing, we separately conducted a sex-stratified analysis. We also tested multiplicative race and income interactions using the same approach. As a secondary analysis, we examined race differences for the exact place of death (i.e., at home, or in undefined place) for out-of-hospital incident CHD.
We then constructed Cox marginal structural models to examine the mediating role of income using inverse probability weighting23,24. In our mediation analysis, we hypothesized that income is a mediating factor on the pathway between race and the incident CHD outcomes. Inverse probability weighting allowed us to avoid violation of a major mediation analysis assumption,25 which requires careful adjustment of mediator-outcome confounders affected by (or associated with) the exposure25. As seen in the directed acyclic graph in Figure 1, since race, as the exposure, is an upstream variable, there could be a path (path 1) from race to cardiovascular risk factors, which could also be confounders of the association between income and incident CHD (through paths 2 and 5). Therefore, simply adjusting for all covariates in the models could lead to biased results for mediation analysis. The use of methods such as inverse probability weighting, which allows separating the effect of income from the effect of other covariates, is recommended to get less biased estimates24,26. We estimated inverse probability weights using logistic models where income was the outcome. We added cardiovascular risk factors to these logistic models and derived stabilized inverse probability weights to be included in our Cox marginal structural models. In sensitivity analyses, we used different binary cut-points of income to examine whether our conclusions change or remain the same. Missing data were < 5 % for income and other covariates. Individuals with missing income or other covariates were excluded from the analysis. All analyses were conducted in SAS version 9.4.
Figure 1.
Directed acyclic graph as a conceptual model demonstrating race and incident coronary heart disease associations through income as the mediator and other covariates
Abbreviations: CVD: cardiovascular disease, BMI: body mass index, CHD: Coronary heart disease, HT: Hypertension
An institutional review board at each site approved the ARIC study, and study participants provided written informed consent at all study centers. We also obtained approval from the Emory University Institutional Review Board (IRB00111905).
Results
The characteristics of the study population by race are described in Table 1. Among participants, 43 % were men, and 27 % were Black. Black participants were slightly younger; the mean (SD) age was 53.4 (5.8) for Black participants and 54.2(5.7) for White participants. There were large differences in education and income by race. Among Black participants, 52.4 % had an annual income of < $16000; that figure was 12.2 % among the White participants. Smoking status and prevalence of hypercholesterolemia were similar by race, but Black individuals had a higher BMI and a higher prevalence of hypertension and diabetes.
Table 1.
Characteristics of Atherosclerosis Risk in Communities cohort study participants at baseline (1987–89) by race (n=14979).
| Black participants1 (n=4095) | White participants1 (n=10884) | |
|---|---|---|
| Age 2 , mean (SD), y | 53.4 (5.8) | 54.2 (5.7) |
| Education, N (%) | ||
| Grade school or less | 805 (19.7 %) | 580 (5.3 %) |
| High school, but no degree | 884 (21.7 %) | 1212 (11.1 %) |
| High school graduate | 881 (21.6 %) | 3975 (36.6 %) |
| Vocational school | 278 (6.8 %) | 980 (9.0 %) |
| College | 708 (17.3 %) | 3135 (28.8 %) |
| Graduate school or Professional school | 527 (12.9 %) | 989 (9.1 %) |
| Income (US $), N (%) | ||
| <16000 | 1931 (52.4 %) | 1272 (12.2 %) |
| 16000 to < 25000 | 666 (18.1 %) | 1457 (14.0 %) |
| 25000 to < 35000 | 466 (12.6 %) | 2034 (19.5 %) |
| 35000 to < 50000 | 360 (9.8 %) | 2393 (23.0 %) |
| ≥ 50000 | 262 (7.1 %) | 3259 (31.3 %) |
| Smoking status N (%) | ||
| Current | 1212 (29.7 %) | 2688 (24.7 %) |
| Former | 951 (23.3 %) | 3733 (34.3 %) |
| Never | 1924 (47.1 %) | 4455 (41.0 %) |
| Body Mass Index, N (%) | ||
| < 30.0 | 2423 (59.4 %) | 8434 (77.6 %) |
| ≥ 30.0 | 1653 (40.6 %) | 2439 (22.4 %) |
| Hypertension, N (%) | 2252 (55.3 %) | 2844 (26.2 %) |
| Diabetes, N (%) | 753 (18.9 %) | 922 (8.5 %) |
| Total Cholesterol, N (%) | ||
| < 200 mg/dl | 1559 (40.2 %) | 4025 (37.1 %) |
| ≥ 200 mg/dl | 2322 (59.8 %) | 6830 (62.9 %) |
Abbreviations: SD: standard deviation
All analyses were restricted to people with no previous history of coronary heart disease at baseline.
Age is the age of the participant at baseline.
Table 2 shows the association of race with incident fatal, non-fatal, and total CHD events in the ARIC Cohort. The fatal CHD incidence was higher in Black participants (3.5 per 1000 person years, (95 % CI, 3.1–3.9) than in White participants (2.1, 95 % CI, 1.9–2.2). Comparing Black to White participants, the hazard ratio of fatal incident CHD was 2.02 (1.75–2.33) in age and sex-adjusted models and attenuated to 1.39 (1.17–1.64) after income was included in Model 2. Racial differences in fatal CHD disappeared in Model 3 (HR, 1.01, 95 % CI, 0.84–1.21) after both income and cardiovascular risk factors were included. In contrast, the non-fatal CHD incidence per 1000 person-years was similar by race; the age and sex-adjusted hazard ratio comparing Black to White participants was 1.05 (0.93–1.18). Overall, the total incident CHD rate was higher in Black versus White participants. In sex- and age- adjusted models, the hazard ratio was 1.36 (95 % CI, 1.24–1.49) comparing Black versus White participants. The hazard ratio attenuated to 1.06 (0.96–1.18) after income was included in the model and further attenuated to 0.88 (0.79–0.99) in fully-adjusted multivariable Model 3.
Table 2.
Association of race with incident non-fatal, fatal and total coronary heart disease in the Atherosclerosis Risk in Communities cohort study (1987–2017) (n=14979)
| Black participants (n=4095) | White participants (n=10884) | |
|---|---|---|
| Person-years | 87327 | 249663 |
| Incident fatal coronary heart disease | ||
| Events | 305 | 511 |
| Incidence (9 % CI) per 1000 person-years | 3.50 (3.11–3.90) | 2.05 (1.88–2.23) |
| Model 11, HR (95% CI) | 2.02 (1.75–2.33) | ref |
| Model 22, HR (95% CI) | 1.39 (1.17–1.64) | ref |
| Model 33, HR (95% CI) | 1.01 (0.84–1.21) | ref |
| Incident non-fatal coronary heart disease | ||
| Events | 347 | 1069 |
| Incidence (95 % CI) per 1000 person-years | 3.97 (3.57–44.1) | 4.28 (4.03–4.54) |
| Model 11, HR (95% CI) | 1.05 (0.93–1.18) | ref |
| Model 22, HR (95% CI) | 0.89 (0.77–1.02) | ref |
| Model 33, HR (95% CI) | 0.80 (0.69–0.93) | ref |
| Total incident coronary heart disease | ||
| Events | 652 | 1580 |
| Incidence (95 % CI) per 1000 person-years | 7.47 (6.91–8.06) | 6.33 (6.02 −6.65) |
| Model 11, HR (95% CI) | 1.36 (1.24–1.49) | ref |
| Model 22, HR (95% CI) | 1.06 (0.96–1.18) | ref |
| Model 33, HR (95% CI) | 0.88 (0.79−0.99) | ref |
Abbreviations: HR: Hazard ratio, CI: Confidence interval
Model 1 is Cox proportional hazard model, adjusted for age and sex.
In Model 2, income is included in addition to Model 1. Income was included in five groups: < $16000, $16000 to $25000, $25000 to $35000, $35000 to $50000, ≥ $50000
In Model 3, cardiovascular risk factors (smoking, BMI, hypertension, diabetes, total cholesterol) are additionally included to Model 2. All analyses were restricted to people with no previous history of coronary heart disease at baseline.
Both fatal out-of-hospital and fatal in-hospital CHD were higher in Black vs. White participants (Figure 2). The risk for fatal out-of-hospital CHD was higher in Black than White participants in sex and age- adjusted models (HR, 1.65, 95 % CI, 1.32–2.07) (Table 3). The magnitude of the race difference was higher for fatal in-hospital CHD than for fatal out-of-hospital CHD (HR, 2.37, 95 % CI, 1.96–2.86). However, after income was included in the models, racial differences largely disappeared for fatal out-of-hospital CHD (HR:1.06, 95 % CI, 0.82–1.37), whereas differences persisted for fatal in-hospital CHD (HR: 1.73, 95 % CI, 1.39–2.16). In fully-adjusted multivariable models, the HRs attenuated to 0.77 (0.58–1.02) for fatal out-of-hospital CHD and to 1.24 (0.98–1.58) for fatal in-hospital CHD (Table 3). Also, in fully adjusted models, compared to those with income ≥ 50000, the participants in lower income groups had higher risk for both fatal out-of-hospital and in-hospital CHD. The magnitude of hazard ratios was particularly elevated for those in the lowest income groups (< $16000) for both fatal out-of-hospital CHD (HR, 2.76, 95 % CI, 1.92–3.95) and for fatal in-hospital CHD (HR, 1.95, 95 % CI, 1.42–2.67). Income was a predictor of both outcomes (Supplementary Table 1).
Figure 2.
Incidence of non-fatal, fatal out-of-hospital and fatal in-hospital coronary heart disease in Black and White participants in ARIC Cohort (1987–2017)
Abbreviation: CHD: Coronary heart disease
Table 3.
Association of race with fatal out-of-hospital and in-hospital coronary heart disease in the Atherosclerosis Risk in Communities cohort study (1987–2017) (n=14979)
| Black participants (n=4095) | White participants (n=10884) | |
|---|---|---|
| Person years | 87327 | 249663 |
| Fatal out-of-hospital incident coronary heart disease 1 | ||
| Events | 116 | 240 |
| Incidence (95 % CI) per 1000 person-years | 1.33 (1.10–1.59) | 0.96 (0.85–1.09) |
| Model 12, HR (95% CI) | 1.65 (1.32–2.07) | ref |
| Model 23, HR (95% CI) | 1.06 (0.82–1.37) | ref |
| Model 34, HR (95% CI) | 0.77(0.58–1.02) | ref |
| Fatal in-hospital incident coronary heart disease 5 | ||
| Events | 189 | 267 |
| Incidence (95 % CI) per 1000 person-years | 2.16 (1.87–2.49) | 1.07 (0.95–1.20) |
| Model 12, HR (95% CI) | 2.37 (1.96–2.86) | ref |
| Model 23, HR (95% CI) | 1.73 (1.39–2.16) | ref |
| Model 34, HR (95% CI) | 1.24 (0.98–1.58) | ref |
Abbreviations: HR: Hazard ratio, CI: Confidence interval
Fatal out-of-hospital coronary heart disease include deaths of participants who died at home, nursing homes, other undefined place or who were dead on arrival to hospital. All analyses were restricted to people with no previous history of coronary heart disease at baseline.
Model 1 is Cox proportional hazard model, adjusted for age and sex.
In Model 2, income is included in addition to Model 1. Income was included in five groups: < $16000, $16000 to $25000, $25000 to $35000, $35000 to $50000, > $50000
In Model 3, cardiovascular risk factors (smoking, BMI, hypertension, diabetes, total cholesterol) are additionally included to Model 2. All analyses were restricted to people with no previous history of coronary heart disease.
Fatal in-hospital coronary heart disease includes deaths which occurred in hospital
Among those hospitalized, the case-fatality for incident CHD was also elevated in Black patients compared with White patients (HR, 1.82, 95 % CI, 1.42–2.32) (Supplementary Table 2). There was a significant interaction between race and sex for non-fatal CHD (p: 0.003) and total CHD (p: 0.042) but not for fatal CHD. The findings from the models which we created to test interaction are presented in Supplementary Tables 3–5. The findings of the sex-stratified analysis are presented in Figure 3. In sex-stratified analysis, among both men and women, the racial difference in fatal out-of-hospital CHD was higher than the racial difference in fatal in-hospital CHD (Figure 3). There were no significant interactions between race and income.
Figure 3.
Results from sex-stratified analysis comparing racial differences in incident CHD outcomes among men and women adjusted for age in ARIC Cohort (1987–2017)
Abbreviations: HR: Hazard Ratio, CHD: Coronary Heart disease
In secondary analysis, the attenuation in the hazard ratios after including cardiovascular factors (without income) to the models was similar to the attenuation in hazard ratios after including income (without cardiovascular risk factors). These results suggest that income and cardiovascular risk factors are interlinked and income is likely a proximal exposure leading to higher levels of cardiovascular risk factors (Supplementary Tables 6 and 7).
In secondary analyses of out-of-hospital deaths, most Black and White participants died in their homes, but Black individuals were more likely to die than White individuals whether the death occurred at home (HR, 1.84, 95 % CI, 1.36–2.48) or in an undefined place (HR, 2.07, 95 % CI, 1.26–3.39) (Supplementary Table 8).
In inverse probability weighted Cox marginal structural models, where income was included as a mediator, the income-controlled direct effects of race in Black vs. White participants was 0.96 (0.83–1.11) for incident non-fatal CHD and was 1.68 (1.41–2.00) for incident fatal CHD. The racial disparities also attenuated for both fatal out-of-hospital CHD (HR: 1.33, 95 % CI, 1.01–1.74) and for fatal in-hospital CHD (HR: 2.03, 95 % CI, 1.61–2.55) (Table 4).
Table 4.
Income-controlled direct effects of race on incident CHD in Atherosclerosis Risk in Communities cohort (1987–2017) (n=14979)
| Black participants (n=4095) | White participants (n=10884) | |
|---|---|---|
| Incident fatal coronary heart disease | ||
| HR1 (95% CI) | 1.68 (1.41–2.00) | ref |
| HR2 (95% CI) | 1.54 (1.27–1.86) | ref |
| HR3 (95% CI) | 1.49 (1.21–1.82) | ref |
| Incident non-fatal coronary heart disease | ||
| HR1 (95% CI) | 0.96 (0.83–1.11) | ref |
| HR2 (95% CI) | 0.93 (0.79–1.09) | ref |
| HR3 (95% CI) | 0.95 (0.81–1.12) | ref |
| Total incident coronary heart disease | ||
| HR1 (95% CI) | 1.20 (1.07–1.34) | ref |
| HR2 (95% CI) | 1.13 (1.00–1.28) | ref |
| HR3 (95% CI) | 1.13 (1.00–1.28) | ref |
| Fatal out-of-hospital incident coronary heart disease 4 | ||
| HR1 (95% CI) | 1.33 (1.01–1.74) | ref |
| HR2 (95% CI) | 1.17 (0.87–1.57) | ref |
| HR3 (95% CI) | 1.12 (0.84–1.49) | |
| Fatal in-hospital incident coronary heart disease 5 | ||
| HR1 (95% CI) | 2.03 (1.61–2.55) | ref |
| HR2 (95% CI) | 1.93 (1.51–2.48) | ref |
| HR3 (95% CI) | 1.88 (1.43–2.47) | ref |
Abbreviations: HR: Hazard ratio: CI: Confidence interval
HR is estimated with a Cox marginal structural model where income (categorized as ‘< $35000 and ‘$35000 and above’) is included as a mediator to the model. Inverse probability weighting method is applied. Other covariates include age, sex, and cardiovascular risk factors (smoking, BMI, hypertension, diabetes, total cholesterol). All analyses were restricted to people with no previous history of coronary heart disease at baseline.
HR is estimated with the same Cox marginal structural model as above. Income is categorized as ‘< $25000’ and ‘$25000 and above’ for sensitivity analysis.
HR is estimated with the same Cox marginal structural model as above. Income is categorized as ‘< $16000’ and ‘$16000 and above’ for sensitivity analysis.
Fatal out-of-hospital coronary heart disease include deaths of participants who died at home, nursing homes, other undefined place or who were dead on arrival to hospital.
Fatal in-hospital coronary heart disease include deaths which occurred in-hospital.
Our conclusions remained similar when we regrouped income in the same models for a sensitivity analysis (Table 4).
Discussion
In this community-based cohort study, the incidence of both fatal out-of-hospital and fatal in-hospital CHD was higher in Black versus White individuals. The racial disparity was greatest for in-hospital fatal CHD and thus case-fatality of those hospitalized. The effect of income in explaining racial disparities was similar for fatal out-of-hospital CHD and fatal in-hospital CHD. These findings have implications for prevention and policy regarding access to care and appropriateness of clinical care and prevention strategies for potentially under-served groups such as the Black population.
We show that the lower income of Black individuals plays an important role in explaining race differences in CHD death. In agreement with our results, income previously was reported to be the main driver of racial differences in sudden cardiac arrest in other investigations20,21. Furthermore, lower income has been associated with lower awareness of CHD, including the alarming symptoms of an AMI27. Our findings extend this literature to out-of-hospital death as a whole, and suggest a potential role for access to care, as a lower access to health care due to limited income could cause delays in seeking care or even discourage care altogether28.
The higher rates of fatal incident CHD in our study parallel previous reports that the first clinical presentation of CHD is more fatal among Black individuals compared with Whites1,3,11. One reason for the higher rate of fatal CHD in Black than in White individuals could be a higher rate of sudden cardiac death among Black people. Sudden cardiac death was indeed almost twice as high in Black than in White participants in previous analyses of the ARIC20 and the REGARDS studies29. However, we found an excess of mortality among Black individuals for both out-of-hospital and in-hospital death, therefore it is unlikely that the higher rate of fatal CHD in Black persons is simply a reflection of a higher rate of sudden cardiac death.
A second explanation for racial differences in incident fatal CHD could be due to differences in the time between symptom onset and arrival to the hospital,30 since significant delays in seeking medical care could increase the possibility of death from CHD. Based on previous studies, Black individuals tend to have longer prehospital delays31,32 and are more likely to be unaware of the symptoms of an incipient CHD event27 compared with White individuals. Also, previous studies suggest that Black patients with AMI receive lower in-hospital quality of care with higher readmission rates than their White counterparts33. Additionally, previous studies suggested that significant racial disparities exist in utilization and outcomes of cardiac surgery34,35 where Black individuals are disadvantaged compared to Whites. These factors could lead to a higher incidence of in-hospital CHD and case-fatality in Black individuals compared to White individuals as suggested by our findings in this study.
A third possible explanation is that Black individuals have a higher prevalence of major CHD risk factors and lower rates of access to interventions aimed at controlling these risk factors compared to White counterparts36–38. Previous literature reported higher in-hospital mortality and lower secondary prevention uptake, such as revascularization procedures in Black individuals compared to White individuals12–19. Furthermore, Black patients are reported to have longer waiting times to treatment after hospitalization than White patients39, resulting in delays for the receipt of secondary prevention interventions which could contribute to higher mortality40. The higher rates of fatal in-hospital CHD and of case-fatality in Black vs. White individuals in our analysis are consistent with previous studies8,41,42. Race-related disparities in fatal in-hospital CHD lost statistical significance after adjusting for cardiovascular risk factors, suggesting that cardiovascular risk factors play a role to some extent in explaining outcome differences by race.
Our study has several strengths, including the large sample size and the long duration of follow-up in a community-based setting. Another strength was the use of self-reported race, as suggested by recent guidelines for disparities research,43,44 rather than inferring race from other sources. We used rigorous methods for mediation analysis with marginal structural models to help avoid potential biases. Furthermore, the ARIC study has active surveillance of events through hospital records and adjudication by an expert committee, minimizing event misclassification. For the adjudication of out-of-hospital incident CHD deaths, the ARIC study incorporated multiple sources of information, including interviews with the next of kin and physicians. However, a limitation is that all participants in the Jackson site were Black, and participants in the Minnesota and Maryland sites were predominantly White; therefore, we were not able to fully separate differences by race from differences by study site. Also, we could only consider baseline socioeconomic and cardiovascular risk factors in our analysis and we did not examine potential role of racial differences in treatments and procedures on the study results. It is likely that other environmental, social, cultural and policy factors could play a role in the excess CHD death among Black persons. Further studies are needed to investigate how the geographical and contextual factors would impact the association of race and CHD incidence.
In conclusion, based on our findings, Black individuals die from CHD at about twice the rate of White individuals, and the excess in mortality is seen irrespective of where these events occur in or out of the hospital. Income plays a pronounced role in this disparity for both in- and out-of-hospital deaths, also suggesting a key role of healthcare access. These findings highlight the need for better primary prevention interventions among Black people to prevent CHD death. Our results also suggest the importance of targeting lack of healthcare coverage and other potential barriers to access to care in order to decrease racial differences in CHD death and foster health equity. Timely access to emergency care and effective preventive interventions could decrease the racial disparities in fatal CHD events. Furthermore, equal access to high quality of in-hospital care, and to advanced cardiology care, such as cardiac surgery when needed, could prevent racial disparities in in-hospital fatal CHD and its case-fatality.
Supplementary Material
Acknowledgments
The authors thank the staff and participants of the ARIC study for their important contributions.
Sources of Funding
The ARIC study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. (HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, HHSN268201700004I). Dr Duygu Islek is funded by the American Heart Association pre-doctoral fellowship (Award number: 19PRE34380062). Dr. Mohammed K. Ali is partially supported by the Georgia Center for Diabetes Translation Research funded by the National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024). Research reported in this publication was also supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number K24HL148521. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funding sources had no role in study design; in the collection, analysis, and interpretation of data; in writing the report; and in the decision to submit the article for publication.
Footnotes
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Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Disclosures
None.
Supplemental Materials
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