Abstract
Background:
The prevalence of heart failure (HF) is increasing among young adults in the United States with pervasive racial and ethnic differences in this population.
Objective:
To evaluate contemporary associations between race and ethnicity, clinical comorbidities, and outcomes among young to middle-aged adults with HF.
Methods:
A retrospective analysis was performed using the National Health and Nutrition Examination Survey. All participants with a self-report of HF aged 20–64 years from 2005 to 2018 were included and stratified by race and ethnicity [non-Hispanic (NH) Whites, NH Blacks, and Hispanics]. Data on baseline characteristics including age, sex, marital status, citizenship, education level, body mass index, insurance, waist circumference, cigarette smoking, marijuana use, and relevant clinical comorbidities were included. Weighted logistic regression was performed to estimate adjusted odds ratios (aOR) to determine the association of race and ethnicity with HF. Cox proportional-hazards models were used to assess the association of race and ethnicity with all-cause and cardiac mortality.
Results:
A total of 1,940,447 young to middle-aged adults had self-reported HF between 2005 and 2018, of whom 61% were NH White, 40% were NH Black, and 22% were Hispanic. When compared with NH White adults, NH Black adults had higher odds of HF adjusted for age, sex, insurance status, marital status, education level, citizenship status, and clinical comorbidities (adjusted aOR 2.63, 95% CI: 1.71–4.05, p < 0.001). There was no significant difference in the odds of HF between Hispanic and NH White adults (aOR 1.18, 95% CI: 0.64–2.18, p = 0.585). NH Black adults had higher mean systolic and diastolic blood pressure, and a comparable or lower burden of cardiovascular and non-cardiovascular clinical comorbidities compared with NH White and Hispanic adults. No statistical significance was noted by race and ethnicity for all-cause and cardiac mortality during a follow-up of 5 years.
Conclusion:
NH Black young to middle-aged adults were more likely to have HF which may be related to higher blood pressure given the largely similar burden of clinically relevant comorbidities compared with other racial and ethnic groups.
Keywords: epidemiology, heart failure, hypertension, outcomes, young adults
Heart failure (HF) is the second most common cause of hospitalizations in the United States and afflicts approximately 7 million individuals, with a rising trend in mortality in recent years.1–4 Historically, HF was considered to be a disorder of the elderly; however, there has been an appreciable increase in the burden of HF among young individuals in recent years, which reflects a change in HF epidemiology. 5 HF inequities span across races and ethnicities; Black individuals have the highest HF prevalence compared to other races,6,7 with recent studies suggesting that this disparity may also be prevalent among young adults. 8 Black, American Indian, and Alaska Native individuals have a higher risk of all-cause HF-related death compared with other racial/ethnic groups; notably, there has been a greater increase in HF-related deaths among Black individuals compared to other races and ethnicities from 2010 to 2020, especially among patients aged 65 or lower. 4 Herein, we sought to assess the demographic differences in prevalence and outcomes in ambulatory young to middle-aged adults with HF in the United States.
Methods
The NHANES study design, operation, and contents have been published previously and are available online. Participants of the survey provide samples representative of non-institutionalized US populations based on complex sampling methods used by the National Center for Health Statistics (NCHS). 9 We conducted a retrospective analysis of NHANES between 2005 and 2018. HF was defined based on self-report in response to ‘Has a doctor or other health professional ever told you that you had congestive heart failure?’. Adults 20–64 years who identified as non-Hispanic (NH) White, NH Black, or Hispanic (Mexican-American and other Hispanics) were included in this analysis. Baseline characteristics including age, sex, education level, body mass index (kg/m2), insurance, waist circumference (inches), marital status, citizenship, cigarette smoking, and marijuana use were included. Self-reported comorbidities including hypertension, dyslipidemia, cancer, stroke, diabetes mellitus, coronary artery disease, chronic obstructive pulmonary disease, obesity, and arthritis were recorded.
Descriptive statistics were used to summarize the continuous and categorical variables. The weighted mean and standard error were used for continuous variables, and the categorical variables were expressed as unweighted frequencies and weighted percentages. Univariate analyses for between-group comparisons used the Rao-Scott chi-square test for categorical variables (e.g. sex and citizenship status) and weighted simple linear regression for continuous variables (e.g. age). Weighted logistic regression was performed to estimate unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) to determine the association between race/ethnicity and self-reported HF. Model 1 was adjusted for age and sex. Model 2 was adjusted for age, sex, and health insurance (yes or no). Model 3 was adjusted for age, sex, health insurance (yes or no), marital status, citizenship status, level of education, and the presence of clinical comorbidities (diabetes mellitus, hypertension, coronary artery disease, stroke, obesity, dyslipidemia, smoking, and marijuana status).
NHANES is linked to death certificate records from the National Death Index. The public-use linked mortality file for 1999–2014 NHANES includes follow-up time and underlying cause of death for NHANES adult participants through 31 December 2015. Hence, mortality analysis was restricted to the participants included till 2014. A detailed description of the linkage methodology and analytic guidelines are available on the NCHS data linkage webpage. 10 Cardiac deaths were defined as those with International Classification of Diseases, 10th Revision (ICD-10) codes I00 to I09, I11, I13, and I20 to I51.
We generated Kaplan–Meier survival curves for all-cause mortality and cardiac mortality stratified by race/ethnicity. We used univariate Cox proportional-hazards models to assess the association between race/ethnicity with all-cause and cardiac mortality in participants with HF. Hazard ratios (HRs) and 95% CIs were estimated. Follow-up began at the time of the interview and ended on the date of death or 31 December 2015, whichever came first. We then used multivariable models to adjust for age and sex. Using Stata 16.1 (StataCorp, College Station, TX, USA), our analyses accounted for survey design complexity by incorporating sampling weights, primary sampling units, and strata. This allowed us to estimate population proportions, means, and regression coefficients using svy commands.
Results
Between 2005 and 2018, there were a total of 1,940,447 weighted participants (unweighted 454) with HF between the ages of 20–64 years. Of these participants, 1,180,184 (60.8%) were NH White, 509,966 (40.1%) were NH Black, and 250,297 (21.8%) were Hispanic. The baseline characteristics of included participants are summarized in Table 1. Comorbidities were generally similar among NH Black adults with HF compared with NH White adults and Hispanic adults (Table 2). NH Black adults tended to have higher systolic and diastolic BP compared with NH White adults and Hispanic adults (systolic BP 132.5 ± 2.0 mmHg versus 123.6 ± 1.6 mmHg, p = 0.002; diastolic BP 76.9 ± 1.2 mmHg versus 71.1 ± 0.9 mmHg, p = 0.001). NH Black adults were found to have a marginally higher prevalence of hypertension compared to other races nearing statistical significance (92.8% versus 83.4%; p = 0.056).
Table 1.
Baseline characteristics of the included participants.
| Variables | Non-Hispanic White adults | Non-Hispanic Black adults | Hispanic adults | Total | p Value |
|---|---|---|---|---|---|
| Weighted, n (weighted %) | 1,180,184 (60.8%) | 509,966 (26.3%) | 250,297 (12.9%) | 1,940,447 | |
| Unweighted Sample, n (%) | 173 (38.1%) | 182 (40.1%) | 99 (21.8%) | 454 | 0.381 |
| Age, mean (standard error) | 53.86 (0.77) | 51.23 (0.76) | 51.3 (1.09) | 52.84 (0.51) | 0.038 |
| Age groups, n (weighted %) | 0.643 | ||||
| 20–39 | 17 (11.5%) | 14 (10.7%) | 4 (7.0%) | 35 (10.7%) | |
| 40–64 | 156 (88.5%) | 168 (89.3%) | 95 (93.0%) | 419 (89.3%) | |
| Sex, n (weighted %) | 0.185 | ||||
| Men | 104 (57.1%) | 92 (47.5%) | 54 (55.5%) | 250 (54.4%) | |
| Women | 69 (42.9%) | 90 (52.5%) | 45 (44.5%) | 204 (45.6%) | |
| Education level, n (weighted %) | <0.001 | ||||
| Less than 9th grade | 15 (6.9%) | 7 (4.3%) | 30 (30.0%) | 52 (9.2%) | |
| 9th–11th grade (includes 12th grade with no diploma) | 42 (18.4%) | 41 (22.4%) | 24 (21.9%) | 107 (20.0%) | |
| High school graduate/GED or equivalent | 48 (29.7%) | 55 (30.8%) | 19 (25.0%) | 122 (29.4%) | |
| Some college or AA degree | 52 (33.9%) | 62 (33.9%) | 22 (17.8%) | 136 (31.8%) | |
| College graduate or above | 16 (11.0%) | 17 (8.6%) | 4 (5.3%) | 37 (9.7%) | |
| Insurance, n (weighted %) | 0.154 | ||||
| Yes | 155 (88.9%) | 152 (80.6%) | 80 (81.0%) | 387 (85.7%) | |
| No | 18 (11.1%) | 30 (19.4%) | 19 (19.0%) | 67 (14.3%) | |
| Insurance, not mutually exclusive, n (weighted %) | |||||
| Private | 54 (40.6%) | 44 (22.8%) | 18 (17.0%) | 116 (32.9%) | 0.001 |
| Medicare | 53 (25.4%) | 59 (27.3%) | 25 (24.0%) | 137 (25.7%) | 0.877 |
| Medicaid | 57 (14.0%) | 64 (37.3%) | 29 (34.5%) | 150 (28.9%) | 0.029 |
| BMI, n (weighted %) | 0.275 | ||||
| <18.5 | 3 (1.2%) | 2 (1.5%) | 1 (1.3%) | 6 (1.3%) | |
| 18.5–24.9 | 20 (11.5%) | 29 (18.6%) | 5 (7.4%) | 54 (12.9%) | |
| 25–29.9 | 36 (20.0%) | 27 (17.0%) | 30 (29.8%) | 93 (20.5%) | |
| ⩾30.0 | 100 (67.2%) | 109 (62.9%) | 53 (61.5%) | 262 (65.3%) | |
| Waist circumference, n (weighted %) | 0.566 | ||||
| Normal | 34 (21.0%) | 35 (26.9%) | 18 (23.4%) | 87 (22.8%) | |
| High | 118 (79.0%) | 113 (73.1%) | 64 (76.6%) | 295 (77.2%) | |
| Smoking status, n (weighted %) | 0.001 | ||||
| Never | 39 (28.6%) | 82 (46.6%) | 46 (51.2%) | 167 (36.2%) | |
| Past | 62 (35.6%) | 46 (21.9%) | 38 (28.5%) | 146 (31.1%) | |
| Current daily/nondaily smoker | 72 (35.9%) | 54 (31.6%) | 15 (20.3%) | 141 (32.7%) | |
| Marijuana, n (weighted %) | 0.015 | ||||
| Never | 33 (36.8%) | 43 (41.9%) | 32 (73.6%) | 108 (43.0%) | |
| Former | 51 (51.4%) | 47 (46.0%) | 5 (20.1%) | 103 (45.8%) | |
| Current | 15 (11.8%) | 12 (12.1%) | 3 (6.3%) | 30 (11.2%) |
Unweighted n (weighted %); weighted mean and standard error.
BMI, body mass index.
Table 2.
Prevalence of comorbidities among young individuals with heart failure of different races.
| Non-Hispanic White | Non-Hispanic Black | Hispanic | p Value | |
|---|---|---|---|---|
| Hypertension, n (weighted %) | 143 (83.4%) | 164 (92.8%) | 85 (86.4%) | 0.056 |
| Total participants | 170 | 178 | 98 | |
| Mean systolic blood pressure (SE) | 123.6 (1.6) | 132.5 (2.0) | 126.7 (2.5) | 0.002 |
| Mean diastolic blood pressure (SE) | 71.1 (0.9) | 76.9 (1.2) | 75.0 (1.8) | 0.001 |
| Diabetes, n (weighted %) | 76 (44.9%) | 91 (45.3%) | 54 (50.3%) | 0.792 |
| Total participants | 173 | 182 | 99 | |
| Dyslipidemia, n (weighted %) | 114 (64.5%) | 118 (63.5%) | 60 (53.0%) | 0.331 |
| Total participants | 173 | 181 | 99 | |
| Cancer, n (weighted %) | 29 (18.8%) | 17 (7.0%) | 8 (6.0%) | <0.001 |
| Total participants | 172 | 182 | 98 | |
| Stroke, n (weighted %) | 37 (19.2%) | 28 (14.4%) | 14 (11.4%) | 0.226 |
| Total participants | 173 | 182 | 98 | |
| Coronary artery disease, n (weighted %) | 111 (60.0%) | 92 (49.6%) | 72 (70.4%) | 0.026 |
| Total participants | 173 | 182 | 99 | |
| COPD, n (weighted %) | 70 (38.5%) | 46 (24.4%) | 29 (29.7%) | 0.049 |
| Total participants | 173 | 182 | 99 | |
| Arthritis, n (weighted %) | 100 (59%) | 96 (50.3%) | 49 (39%) | 0.013 |
| Total participants | 173 | 182 | 99 | |
| Obesity, n (weighted %) | 100 (67.2%) | 109 (62.9%) | 53 (61.5%) | 0.672 |
| Total participants | 159 | 167 | 89 |
Unweighted n (weighted %); weighted mean and SE.
SE, standard error.
When compared with young NH White adults, young NH Black adults had higher unadjusted (unadjusted OR 2.31, 95% CI: 1.79–2.98, p < 0.001) and adjusted odds of HF (adjusted OR 2.63, 95% CI: 1.71–4.05, p < 0.001). There was no statistically significant difference in the odds of HF between young Hispanic adults and young NH White adults (unadjusted OR 0.86, 95% CI: 0.59–1.26, p = 0.446; unadjusted OR 1.18, 95% CI: 0.64–2.18, p = 0.585) (Table 3).
Table 3.
Prevalence odds of heart failure across different racial and ethnic groups using a linear regression model.
| Race/ethnicity | Unadjusted odds ratio (95% CI) | p Value | Adjusted odds ratio* (95% CI) | p Value |
|---|---|---|---|---|
| NH White (reference) | ||||
| NH Black | 2.31 (1.79–2.98) | <0.001 | 2.63 (1.71–4.05) | <0.001 |
| Hispanic | 0.86 (0.59–1.26) | 0.446 | 1.18 (0.64–2.18) | 0.585 |
Model adjusted for diabetes mellitus, hypertension, coronary artery disease, stroke, obesity, dyslipidemia, smoking, and marijuana status.
Compared to NH White adults with HF, there was no significant difference in all-cause mortality for NH Black adults (adjusted HR 0.89, 95% CI: 0.51–1.56, p = 0.695) or Hispanic adults (adjusted HR 0.76, 95% CI: 0.36–1.62, p = 0.478) during a mean 5.2 years of follow-up. Moreover, there was no significant difference in cardiac mortality among NH Black adults (adjusted HR 0.91, 95% CI: 0.35–2.35, p = 0.844) or Hispanic adults (adjusted HR 0.90, 95% CI: 0.25–3.26, p = 0.867) when compared with NH White adults during a mean 5.3 years of follow-up (Figure 1).
Figure 1.
Kaplan–Meier curve shows (a) cardiac mortality and (b) all-cause mortality among young individuals with heart failure of different races.
NH, non-Hispanic.
Discussion
We report several key findings in this analysis of more than 1.9 million weighted young to middle-aged individuals with HF. First, young NH Black adults have twofold higher odds of HF compared with NH White adults of the same age. Second, despite this excess risk, NH Black adults with HF tend to have a similar prevalence of clinically relevant comorbidities compared with White adults and Hispanic adults with HF. Third, mortality across all racial groups was low and no significant difference in all-cause mortality or cardiac mortality was observed between the different racial groups.
Our results are consistent with a 1985–2005 analysis from the Coronary Artery Risk Development in Young Adults (CARDIA) study showing a substantially higher risk of HF among young Black compared to young White adults and expands on this analysis by showing a continuation of this trend for the period of 2005–2018. 8 While prior studies have consistently shown a higher prevalence of hypertension among Black adults compared with White adults, 11 which has been considered a major driver of the increased risk of HF among Black adults of all ages, 7 our study only showed a marginally higher prevalence of hypertension in Black adults with HF. The available data cannot determine the reason for these differences but may be related to underdiagnosis, greater severity, or effect modification due to exposures related to social determinants of health. 12 It is important to note that both systolic and diastolic blood pressures measured during the examination were significantly higher in NH Black adults compared to other races/ethnicities supporting prior research on the relationship between higher blood pressures and risk of HF among NH Black adults. 12
A higher prevalence of HF among Black individuals may be explained by differences in clinical comorbidities and inherent differences in social determinants of health. 7 Although our study showed minimal differences in the prevalence of relevant comorbidities between different races and ethnicities, Black individuals are known to have a higher prevalence of modifiable risk factors like hypertension, obesity, and chronic kidney disease that occur at an earlier age than other races and ethnicities, which likely predisposes them to developing HF at an earlier age.8,13,14 Disproportionate lack of accessibility and affordability due to socioeconomic constraints precludes Black individuals from receiving optimal care for the management of these chronic conditions. 7 There is also a lower inclination toward a healthy lifestyle behavior among Black individuals, as only 20% were reported to have five cardiovascular health metrics at optimal levels, which is lower compared to both White and Hispanic individuals. 15
All-cause and cardiac-related death rates were not different among all races. In contrast to our analysis, previous studies have shown low short-term and long-term mortality in Black patients after HF hospitalization as compared to White patients.16–18 However, findings for mortality from our study need to be interpreted with caution as these data were self-reported, the severity of HF was unknown, and event rates for both all-cause and cardiac-related mortality were low across all racial groups due to young age. Other limitations of this study include its retrospective observational nature, and not accounting for unmeasured confounding factors that may have influenced our findings. Moreover, in addition to using objective parameters in establishing the status of some variables, such as the use of hemoglobin A1c in establishing diabetes status and recorded BP in establishing hypertension status, self-reporting was also used in establishing the status of these variables, which could have led to over- or underestimation of true prevalence. HF was not classified into HF with reduced or preserved ejection fraction, which would have provided epidemiological insight into the phenotypic differences across races and ethnicities.
Conclusion
There are significant disparities in HF among young to middle-aged individuals with Black adults being at a significantly greater risk of HF despite a comparable burden of comorbidities across all racial groups, whereas there was no difference in the risk of HF between NH White adults and Hispanic adults. Further studies are needed to validate these findings and explore factors responsible for a socially vulnerable population being at increased risk for HF.
Acknowledgments
None.
Footnotes
ORCID iDs: Talal Almas 
https://orcid.org/0000-0002-8867-600X
Adeena Jamil
https://orcid.org/0000-0002-2729-0189
Contributor Information
Khawaja M. Talha, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
Talal Almas, Department of Medicine, Harrington Heart & Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
Husam Salah, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA.
Adeena Jamil, Department of Medicine, Dow International Medical College, Dow University of Health Sciences, Karachi, Pakistan.
Heather M. Johnson, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA
Vardhmaan Jain, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA.
Steve Antoine, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Sadiya S. Khan, Division of Cardiology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Steve Antoine is currently affiliated to Division of Cardiology, Michael E DeBakey VA Medical Center, Houston, TX, USA.
Muhammad Shahzeb Khan, Division of Cardiology, Duke University School of Medicine, 2301 Erwin Road, Durham, NC 27710, USA.
Declarations
Ethics approval and consent to participate: Not applicable.
Consent for publication: Not applicable.
Author contributions: Khawaja M. Talha: Data curation; Investigation; Software; Visualization; Writing – original draft.
Talal Almas: Conceptualization; Data curation; Visualization; Writing – original draft; Writing – review & editing.
Abdul Mannan Khan Minhas: Data curation; Investigation; Validation; Visualization.
Husam Salah: Conceptualization; Methodology; Writing – original draft.
Adeena Jamil: Data curation; Formal analysis; Supervision; Validation.
Heather M. Johnson: Conceptualization; Data curation; Formal analysis; Validation; Visualization.
Vardhmaan Jain: Funding acquisition; Investigation; Validation; Visualization; Writing – original draft.
Steve Antoine: Methodology; Validation; Visualization; Writing – original draft; Writing – review & editing.
Sadiya S. Khan: Investigation; Methodology; Project administration; Writing – original draft; Writing – review & editing.
Muhammad Shahzeb Khan: Formal analysis; Funding acquisition; Investigation; Supervision; Visualization; Writing – original draft; Writing – review & editing.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
The authors declare that there is no conflict of interest.
Availability of data and materials: Not applicable.
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