Social Determinants of Health and Comorbidities Among Individuals with Atherosclerotic Cardiovascular Disease: The Behavioral Risk Factor Surveillance System Survey

Abstract

Individuals with atherosclerotic cardiovascular disease (ASCVD) often have a high burden of comorbidities. Social determinants of health (SDOH) may complicate adherence to treatment in these patients. This study assessed the association of comorbidities and SDOH among individuals with ASCVD. Cross-sectional data from the 2016 to 2019 Behavioral Risk Factor Surveillance System, a nationally representative US telephone-based survey of adults ages ≥18 years, were used. Cardiovascular comorbidities included hypertension, hyperlipidemia, diabetes mellitus, current cigarette smoking, and chronic kidney disease. Non-cardiovascular comorbidities included chronic obstructive pulmonary disease, asthma, arthritis, cancer, and depression. SDOH associated with being at or above the 75^th percentile of comorbidity burden were analyzed using multivariable adjusted logistic regression models. The study population included 387,044 individuals, 9% of whom had ASCVD. The mean (SD) numbers of total, cardiovascular, and non-cardiovascular comorbidities were 1.97 (1.27), 1.28 (0.74), 0.69 (0.91) among those without ASCVD and 3.28 (1.62), 1.73 (0.91), and 1.54 (1.22) among those with ASCVD, respectively (P < 0.001 for all comparisons). Female gender, household income ≤$75,000, being unemployed, and difficulty accessing health care were significantly associated with a higher burden of comorbidities among those with ASCVD. The mean (SD) numbers of comorbidities for those with 0, 1, 2, and ≥3 of the aforementioned SDOH were 2.89 (1.45), 2.86 (1.47), 3.39 (1.58), and 4.01 (1.73), respectively (P < 0.001). Among persons with ASCVD, the burden of cardiovascular and non-cardiovascular comorbidities is directly proportional to SDOH in any given individual. Clinicians should address SDOH when managing high-risk individuals.

Introduction

Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death in the United States and worldwide, accounting for a high degree of health care-related expenditures.¹ Individuals with ASCVD often have a high burden of cardiovascular and non-cardiovascular comorbidities, and an increased risk of morbidity and mortality.^2,3

Management of patients with multiple comorbidities is more challenging than management of those with a single comorbidity.⁴ Patients with multiple comorbidities often have difficulty adhering to treatment recommendations because of the complexity of regimens, pill burden, and a high burden of cognitive and psychosocial factors.⁵ Therefore, patients with multiple comorbidities require significant coordination between various care teams, significant health care resources, and at times, prioritization of therapies.

This study evaluated the prevalence and burden of cardiovascular and non-cardiovascular comorbidities in a contemporary population of individuals with ASCVD. The study also assessed social determinants of health (SDOH) associated with having a high burden of comorbidities as these may negatively influence patient adherence.

Methods

Study design

The Behavioral Risk Factor Surveillance System (BRFSS) survey is a nationwide telephone-based survey that was established by the Centers for Disease Control and Prevention.⁶ BRFSS is administered to a random sample that is representative of US adult residents older than age 18 years. The survey aims to evaluate chronic health conditions, health-related risk behaviors, and the use of preventive services among US adults. The BRFSS survey is conducted in all 50 states in the United States, the District of Columbia, and the 3 US territories, making it the largest telephone-based survey in the world. Cross-sectional data from the 2016, 2017, 2018, and 2019 BRFSS surveys were used. All variables were self-reported and have been validated against other national survey data.^7,8

This study was exempt from Institutional Review Board approval because it used de-identified data from a publicly available data set.

Assessment of cardiovascular comorbidities

Hypertension was defined as participants reporting having been told they have high blood pressure by a doctor, nurse, or other health professional. Hyperlipidemia was defined as participants reporting having had their cholesterol checked and having been told by a doctor, nurse, or other health professional that it was high. Diabetes mellitus was identified as participants ever being told they had diabetes. Cigarette status was characterized as ever or never, depending on how participants answered the question “Have you smoked at least 100 cigarettes in your entire life?”. Ever smokers were then classified as current if they reported smoking cigarettes either every day or some days. Chronic kidney disease was defined as participants reporting ever being told that they have kidney disease, excluding kidney stones, bladder infection or incontinence.

Assessment of non-cardiovascular comorbidities

Chronic obstructive pulmonary disease (COPD) was identified as participants reporting ever being told they have COPD, emphysema, or chronic bronchitis. Asthma was defined as participants reporting ever being told they have asthma. Arthritis was defined as participants reporting ever having a doctor diagnose them as having some form of arthritis. Cancer was identified if participants reported ever being told they have skin cancer or any other type of cancer. Depression was defined as participants reporting ever being told they have a depressive disorder (including depression, major depression, dysthymia, or minor depression).

Assessment of SDOH

Demographic variables including health care coverage and living in a metropolitan statistical (urban) area were all self-reported.

ASCVD was identified if participants reported a prior history of coronary heart disease or stroke. Participants were considered to have difficulty accessing medical care if they answered “Yes” to one of the following 3 questions: (1) “Have you delayed getting needed medical care for any of the following reasons in the past 12 months?”; (2) “Was there a time in the past 12 months when you needed to see a doctor but could not because of cost?”; (3) “Not including over the counter (OTC) medications, was there a time in the past 12 months when you did not take your medications as prescribed because of cost?”. US states were classified as having Medicaid expansion if they had done so by the year 2020 based on data from the Kaiser Family Foundation.⁹

Statistical analysis

Prevalence of demographic variables and comorbidities was analyzed using survey weights, as BRFSS used design weighting and iterative proportional fitting in order to ensure representativeness of the data to the US population.¹⁰ Baseline characteristics were summarized using counts (weighted percentages) and stratified by the presence of ASCVD and weighted proportions were compared.

Multivariable logistic regression models were used to evaluate the association of SDOH and having a high burden of comorbidities, defined as the ≥75^th percentile of cumulative comorbidity burden compared to the ≤25^th percentile. SDOH included age, gender, race/ethnicity, education, household income, employment status, living in a metropolitan statistical area, difficulty accessing health care, presence of health care coverage, and living in a state with Medicaid expansion. Factors that were positively associated with having a high burden of comorbidities were classified as 1 if present and 0 if absent. The presence/absence of these sociodemographic features was summed for each individual to calculate a composite score, which was then divided into categories based on the distribution of the data. Mean (standard deviation [SD]) of number of comorbidities stratified by this score also were calculated.

Analyses were conducted using Stata Statistical Software: Release 16.1 (StataCorp LLC, College Station, TX). A P value <0.05 was considered statistically significant.

Results

Baseline characteristics

The study population consisted of 387,044 participants with complete information on comorbidities: 22% were aged ≥65 years; 52% were female; 63% were non-Hispanic White, 12% non-Hispanic Black, and 16% were Hispanic; 9% had ASCVD. Compared to individuals without ASCVD, those with ASCVD were older, more likely to be men, have less than a high school education, have lower income, be unemployed or retired, have health care coverage, report more difficulty accessing health care, and more likely to live in an urban area (all P < 0.001) (Table 1).

Table 1.

Baseline Characteristics of the Study Population by Presence of Atherosclerotic Cardiovascular Disease

	Atherosclerotic cardiovascular disease		P value
	No (N = 338,727; 91%)	Yes (N = 44,681; 9%)	P value
Age (years)			<0.001
18 − 34	53,739 (29%)	677 (4%)
35 − 44	41,898 (17%)	1315 (6%)
45 − 54	56,962 (18%)	3930 (13%)
55 − 64	75,684 (17%)	9959 (25%)
≥65	110,444 (19%)	28,800 (53%)
Gender			<0.001
Men	144,679 (48%)	23,058 (56%)
Women	193,865 (52%)	21,594 (44%)
Race/Ethnicity			<0.001
White	255,663 (63%)	35,056 (72%)
Black	26,842 (12%)	3716 (12%)
Hispanic	27,733 (17%)	2230 (11%)
Other	22,467 (9%)	2779 (5%)
Education			<0.001
Less than high school	20,453 (12%)	4964 (20%)
High school – Some college	180,271 (58%)	27,239 (62%)
More than college	136,867 (30%)	12,348 (18%)
Income			<0.001
<$10,000	11,699 (5%)	2694 (9%)
$10,000−$15,000	12,341 (4%)	3445 (10%)
$15,000−$20,000	18,551 (7%)	4231 (11%)
$20,000−$25,000	23,917 (9%)	4634 (12%)
$25,000−$35,000	28,675 (10%)	4727 (12%)
$35,000−$50,000	40,080 (13%)	5411 (13%)
$50,000−$75,000	46,985 (15%)	4974 (12%)
>$75,000	103,166 (37%)	6957 (20%)
Employment Status			<0.001
Employed	181,058 (60%)	9355 (25%)
Unemployed	51,816 (17%)	11,181 (30%)
Student	8635 (6%)	120 (<1%)
Retired	94,604 (17%)	23,816 (44%)
Presence of Health Care Coverage			<0.001
Yes	313,211 (89%)	42,559 (93%)
No	24,416 (11%)	2010 (7%)
Difficulty Accessing Health Care			<0.001
Yes	36,333 (86%)	5953 (84%)
No	302,394 (14%)	38,728 (16%)
Living in a Metropolitan Statistical Area (urban)			<0.001
Yes	45,618 (82%)	8623 (78%)
No	98,513 (18%)	16,256 (22%)
Living in a State with Medicaid Expansion			0.0002
Yes	250,743 (30%)	31,801 (33%)
No	83,781 (70%)	12,293 (67%)

The median (interquartile range) number of comorbidities among those with ASCVD was 3 (2 − 4). All comorbidities were more prevalent among those with ASCVD compared to those without, with the exception of hyperlipidemia.

The mean (SD) numbers of total, cardiovascular, and non-cardiovascular comorbidities were 1.97 (1.27), 1.28 (0.74), and 0.69 (0.91) among those without ASCVD and 3.28 (1.62), 1.73 (0.91), and 1.54 (1.22) among those with ASCVD, respectively (P < 0.001 for all comparisons). The mean (SD) number of cardiovascular comorbidities was 1.72 and 1.74 for men and women, respectively (P = 0.31). In contrast, there was a higher mean number of non-cardiovascular comorbidities among women (1.34 vs. 1.80; P < 0.001). The mean (SD) number of comorbidities ranged from 2.71 (1.58) among those aged 18 − 34 years to 3.24 (1.52) among those aged ≥65 years (P < 0.001).

Among those with ASCVD, only 2% had no comorbidities, while 11%, 21%, 24%, and 19% had 1, 2, 3, or 4 comorbidities, respectively (Table 2).

Table 2.

Cardiovascular and Non-cardiovascular Comorbidities by Presence of Atherosclerotic Cardiovascular Disease

	Atherosclerotic cardiovascular disease		P value
	No (N = 338,727; 91%)	Yes (N = 44,681; 9%)	P value
Cardiovascular Comorbidities
Hypertension	125,253 (30%)	32,689 (72%)	<0.001
Hyperlipidemia	224,256 (72%)	16,056 (38%)	<0.001
Diabetes mellitus	40,159 (10%)	14,665 (33%)	<0.001
Cigarette smoking	43,469 (14%)	7478 (19%)	<0.001
Chronic kidney disease	9968 (2%)	5196 (12%)	<0.001
Non-Cardiovascular Comorbidities
Chronic obstructive pulmonary disease	21,583 (5%)	10,316 (22%)	<0.001
Asthma	43,507 (13%)	8591 (20%)	<0.001
Arthritis	103,353 (23%)	25,547 (55%)	<0.001
Cancer	55,193 (11%)	13,406 (27%)	<0.001
Depression	62,175 (18%)	12,594 (30%)	<0.001
Cumulative Comorbidity Burden			<0.001
0	16,372 (5%)	800 (2%)
1	110,507 (39%)	4942 (11%)
2	97,033 (28%)	9528 (21%)
3	63,079 (16%)	10,999 (24%)
4	32,017 (8%)	8696 (19%)
5	13,293 (3%)	5408 (12%)
6	4736 (1%)	2830 (6%)
≥7	1690 (<1%)	1478 (<1%)

SDOH and comorbidities

In multivariable adjusted models, female gender, income ≤$75,000, being unemployed, and subjective difficulty accessing health care were all significantly associated with having at least 4 comorbidities among those with ASCVD, while absence of health care coverage was inversely associated (Table 3).

Table 3.

Multivariable Adjusted Odds Ratios (95% Confidence Interval) for the Association of Sociodemographic Factors and Prevalence of a High Burden of Comorbidities Among Individuals with Atherosclerotic Cardiovascular Disease

Age (years)	Odds ratio (95% confidence interval)
18 − 34	1 (ref)
35 − 44	0.78 (0.30,1.99)
45 − 54	0.91 (0.41,2.04)
55 − 64	1.11 (0.52,2.40)
≥65	0.98 (0.45,2.15)
Gender
Men	1 (ref)
Women	1.35 (1.15,1.59)
Race/Ethnicity
White	1 (ref)
Black	0.90 (0.66,1.23)
Hispanic	1.08 (0.71,1.63)
Other	1.01 (0.73,1.41)
Education
Less than high school	1 (ref)
High school – some college	0.93 (0.72,1.21)
More than college	0.76 (0.57,1.01)
Income
<$10,000	2.46 (1.60,3.77)
$10,000−$15,000	2.35 (1.67,3.32)
$15,000−$20,000	2.59 (1.85,3.64)
$20,000−$25,000	1.81 (1.34,2.44)
$25,000−$35,000	2.12 (1.65,2.72)
$35,000−$50,000	1.69 (1.32,2.16)
$50,000−$75,000	1.75 (1.37,2.24)
>$75,000	1 (ref)
Employment Status
Employed	1 (ref)
Unemployed	4.28 (3.33,5.50)
Student	1.12 (0.26,4.78)
Retired	2.11 (1.67,2.67)
Not Living in a Metropolitan Statistical Area (urban)	1.10 (0.94,1.28)
Living in a State with Medicaid Expansion	1.04 (0.87,1.24)
Absence of Health Care Coverage	0.62 (0.39,0.98)
Difficulty Accessing Health Care	1.67 (1.32,2.12)

A composite score was created based on the presence of these SDOH, which ranged from 0 to 4 and was categorized as follows: 0 (5%), 1 (40%), 2 (39%), and ≥3 (16%). The mean (SD) numbers of comorbidities for those with 0, 1, 2, and ≥3 SDOH were 2.89 (1.45), 2.86 (1.47), 3.39 (1.58), and 4.01 (1.73), respectively (P < 0.001).

Discussion

Using a nationally representative US survey, this study found that more than half of individuals with ASCVD have at least 3 comorbidities. Only 2% of individuals with ASCVD had no comorbidity, while 62% had at least 3 comorbidities. Both cardiovascular and non-cardiovascular comorbidities were more prevalent among those with ASCVD. SDOH including female gender, low income, unemployment, and difficulty accessing health care are all significantly associated with having a high burden of comorbidities among individuals with ASCVD.

The present study demonstrated that women were more likely to have a high burden of comorbidities compared to men, driven by a higher burden of non-cardiovascular comorbidities. The number of cardiovascular comorbidities was similar for the 2 gender groups in this study. Prior studies have found that women have a higher number of non-cardiovascular comorbidities such as mental health symptoms¹¹ or cancer.¹² Low income and unemployment may be associated with financial constraints, food insecurity, and limited medical literacy, resulting in difficulty adhering to therapeutic and lifestyle recommendations and having a higher burden of comorbidities. Age was not significantly associated with having a higher number of comorbidities, likely because the number of comorbidities was similar between younger and older individuals (n ∼ 3).

The presence of racial and ethnic disparities in cardiovascular risk factor burden and ASCVD has been well described.^13,14 In addition to directly influencing ASCVD outcomes, SDOH also can result in racial and ethnic health inequities with regard to health outcomes. The present study found no significant association between race/ethnicity and comorbidity burden after adjusting for multiple variables including SDOH. This could potentially indicate that the association of racial differences and comorbidities is at least partly accounted for by variables related to SDOH.¹⁵

Interestingly, this study found that absence of health care coverage was inversely associated with having multiple comorbidities. This could be related to the self-reported nature of the data, whereby those without health care coverage were less likely to be seen by a health care professional and undergo screening tests for risk factors, thereby resulting in underdiagnosis of chronic conditions. Indeed, a prior study found that having health care insurance is associated with increased ASCVD diagnosis.¹⁶ This could be especially important among individuals with ASCVD, who often have multiple coexisting comorbidities. In contrast, the present study found that difficulty accessing health care was associated with a higher number of comorbidities. The authors posit that the presence of health care coverage does not necessarily equate to access to health care. Other factors related to SDOH could determine whether individuals can access the health care system, even in the presence of health care coverage.

Patients with ASCVD and multiple comorbidities may have difficulty accessing the health care system as a result of lack of insurance, unemployment, or subjective difficulty related to lack of transportation or prohibitive costs. Higher risk patients (ie, those with more comorbidities) often are the ones with the least access to care and have the most difficulty paying for medical services, even with health insurance.¹⁷ Other strategies – including offering social services to improve access to care, lowering medication co-pays,¹⁸ improving health literacy and offering screening programs through community engagement efforts using schools,¹⁹ improving the supply of medications, promoting appropriate use of medications, leveraging the services of clinical pharmacists, or providing transportation²⁰ – also can be effective at improving adherence and access to medications in these high-risk patients.²¹

Managing patients with multiple cardiovascular or non-cardiovascular comorbidities often is more challenging than managing those with a single or no comorbidity. The presence of multiple comorbidities also can negatively impact health outcomes as these are often synergistic and can accelerate disease progression. Different comorbidities are treated with different guidelines with complex treatment regimens and recommendations that often can be contradictory and difficult to reconcile by either the patient or the clinician.⁵

Patients with different comorbidities often are prescribed multiple medications,²² which can hinder adherence and also increase the possibility of drug-drug interactions. Management of ASCVD requires 3 to 4 therapies (eg, aspirin, possibly another antiplatelet, statin therapy, possibly an angiotensin-converting enzyme inhibitor [ACE-I] or a beta-blocker). The number of medications is expected to increase with the increasing burden of other non-cardiovascular comorbidities, with concomitant increase in costs and decrease in affordability and adherence. The challenge posed by this risk-access paradox also presents opportunities for improvement. For example, clinicians need to be cognizant of these factors in a patient with multiple comorbidities before adding more therapies. In such patients, clinicians should leverage all available health care resources toward care coordination.

Clinicians also should be mindful of these factors when trying to add multiple therapies for these comorbid patients to ensure that patients are able to afford and able to adhere to those therapies. In some cases, this may mean sequential rather than simultaneous initiation or titration of several therapies. Maximizing therapies that may target several comorbid conditions together (eg, ACE-I for both blood pressure reduction and reduction of chronic kidney disease in a patient with diabetes or sodium-glucose Cotransporter-2 Inhibitors for reduction of CVD, chronic kidney disease, and diabetes mellitus risks) would be one strategy.²³ Fixed-dose combinations also can improve adherence and outcome measures such as cholesterol and blood pressure in patients with multiple comorbidities.²⁴ Lastly, being cognizant of other conditions that are impacting a patient's quality of life (arthritis or depression) also may take precedence as poor control of these also could impact adherence to therapies geared primarily toward ASCVD risk reduction.^25,26

It is also important to acknowledge the effect of SDOH on patients' ability to adhere to treatment recommendations. It is estimated that 20% of an individual's health is determined by the quality of clinical care they receive and their ability to access health care services.²⁷ The remaining 80% is driven by the individual's physical environment, SDOH, and behavioral factors such as exercise or smoking. Therefore, clinicians should screen high-risk patients for SDOH²⁸ and attempt to use available social services to mitigate the influence of these factors, which may correlate directly with a high burden of comorbidities as the current study demonstrates. Earlier interventions among primary prevention patients also can help avoid a progressively increasing burden of comorbidities and development of ASCVD over time.

The 2019 American College of Cardiology/American Heart Association Guideline on the Primary Prevention of Cardiovascular Disease recommends using SDOH to inform optimal implementation of treatment recommendations for the prevention of ASCVD (1-B-NR).²⁹ The same approach should be applied to patients with ASCVD. Patients with ASCVD are recommended for cardiac rehabilitation following hospital discharge (Class I recommendation) to mitigate ASCVD risk and risk factor burden.³⁰ However, adequate provision and adherence to cardiac rehabilitation is affected by SDOH, which can directly influence access to health care. Indeed, a prior study demonstrated that SDOH can affect adherence to physical activity recommendations during cardiac rehabilitation.³¹ Patients with poor SDOH therefore may not derive as much benefit from cardiac rehabilitation. Thus, it is important to recognize the influence of SDOH on health inequities among patients diagnosed with ASCVD as it relates to their ability to participate in cardiac rehabilitation.

A patient-centered approach that incorporates SDOH is essential to deliver effective care for these high-risk individuals.³² This approach not only necessitates a good interpersonal relationship between the patient and the clinician or care team, but also clinical and structural attributes that collectively can influence the patient's experience. For example, increasing patient engagement through shared decision-making, multiple virtual visits, and providing interpretable information can improve adherence in these patients.^33
–35 Building templates in the electronic medical record that incorporate patient values and preferences, and making self-management tools and information easily available to patients also can foster adherence in this high-risk group.¹⁵

As we transition to value-based health care, most payers have started collecting data on their members or beneficiaries to identify social needs that have the potential to influence health care outcomes and costs. For example, the Centers for Medicare & Medicaid Services' Accountable Health Communities Model³⁶ and the Thrive Local initiative by Kaiser Permanente collect information on patients' SDOH and propose a framework to use this information to provide value-based care that meets patients' needs.

Limitations

Study results should be interpreted in the context of important limitations. All variables were self-reported and there was no information available on objective measurements such as blood pressure or plasma glucose and cholesterol for further validation. Therefore, the true prevalence of these risk factors among individuals with ASCVD may have been prone to measurement error and likely is underestimated. BRFSS did not have information on important comorbidities such as heart failure, atrial fibrillation, hypothyroidism, or anemia.

The study definition of ASCVD did not include transient ischemic attacks or peripheral arterial disease because these are not available in BRFSS; therefore, the true prevalence of ASCVD may have been underestimated. Time trend analyses could not be performed given that some risk factors were not evaluated at each BRFSS cycle. Prior data also have shown a lack of awareness of chronic kidney disease³⁷; therefore, the true prevalence of this disease may have been underestimated. Lastly, there is the possibility of residual confounding given the cross-sectional nature of BRFSS.

Conclusion

In conclusion, individuals with ASCVD have a high burden of cardiovascular and non-cardiovascular comorbidities. SDOH including low income, unemployment, and difficulty accessing health care are all associated with having a higher burden of comorbidities. There is a need to identify and address SDOH in a patient-centered approach that will help alleviate the excess burden of morbidity and mortality in this high-risk group.

Footnotes

Authors' Contributions

Dr. Rifai: Conception or design of the work; data collection; data analysis and interpretation; drafting the article; critical review and revision of the article. Dr. Virani: Conception or design of the work; data collection; data analysis and interpretation; drafting the article; critical review and revision of the article; final approval of the version to be published. Drs. Jia, Pickett, Hussain, Navaneethan, Birtcher, Ballantyne, and Petersen: Critical review and revision of the article.

Author Disclosure Statement

Dr. Virani receives research support from the Department of Veterans Affairs, World Heart Federation, Tahir and Jooma Family; and honorarium from the American College of Cardiology (associate editor for Innovations, acc.org). The other authors declare that there are no conflicts of interest.

Funding Information

No funding was received for this article.

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