Understanding Contributors to Racial Disparities in Blood Pressure Control
Background— Racial disparities in blood pressure (BP) control are well documented but poorly understood; prior studies have only included a limited range of potential explanatory factors. We examined a comprehensive set of putative factors related to blood pressure control, including patient clinical and sociodemographic characteristics, beliefs about BP and BP medications, medication adherence, and experiences of discrimination, to determine if the impact of race on BP control remains after accounting for such factors.
Methods and Results— We recruited 806 white and black patients with hypertension from an urban safety-net hospital. From a questionnaire administered to patients after their clinic visits, electronic medical record and BP data, we assessed an array of patient factors. We then examined the association of patient factors with BP control by modeling it as a function of the covariates using random-effects logistic regression. Blacks indicated worse medication adherence, more discrimination, and more concerns about high BP and BP medications, compared with whites. After accounting for all factors, race was no longer a significant predictor of BP control.
Conclusions— Results suggest that equalizing patients’ health beliefs, medication adherence, and experiences with care could ameliorate disparities in BP control. Additional attention must focus on the factors associated with race to identify, and ultimately intervene on, the causes of racial disparities in BP outcomes.
Received March 6, 2009; accepted December 3, 2009.
Hypertension, which affects more than 73 million Americans, is a major risk factor for cardiovascular, cerebrovascular, and renal disease.1 It is more frequent among African Americans2 and accounts for a significant portion of racial differences in mortality, through excess cardiovascular morbidity.3 Many patients with hypertension have poorly controlled blood pressure (BP), and African Americans are disproportionately represented among this group,4 even after controlling for comorbidities such as diabetes and renal disease.4–7
The reason for this racial disparity is not well understood. Many prior studies of BP control have only examined a narrow range of potential etiologic factors—usually clinical characteristics and sometimes including selected sociodemographic factors.8,9 Recently, authors have suggested that patient self-management attitudes and behaviors10 and other attitudes, beliefs, and experiences that might affect medication nonadherence11 might be potential causal pathways to disparities in chronic disease outcomes such as BP control.
Bosworth et al12 proposed an organizing framework for the psychosocial and cultural domains they theorized would affect BP control, incorporating patient characteristics, including age, education, health literacy, and psychological factors such as beliefs and attitudes about health and illness, social/cultural environmental factors, including culturally linked perceptions of hypertension and therapies for it, and the medical environment, including the provider-patient relationship and interactions. The model does not specify causal associations, and, perhaps as a result, it has not been tested empirically, so the presence or strength of the hypothesized associations is not known. The model also did not include comorbid conditions. Thus, we sought to extend this work and the model itself by examining the contribution of the previously proposed and additional putative causal factors, in a more diverse sample in a different setting. We hypothesized that after adjusting for a more extensive set of potential confounders, race would no longer be significantly associated with BP control.
WHAT IS KNOWN
Racial disparities in blood pressure (BP) control are well documented but poorly understood, and prior studies have only included a limited range of potential explanatory factors.
WHAT THE STUDY ADDS
Blacks reported more experiences of discrimination, worse medication adherence, and more concerns about BP.
Patient beliefs about hypertension can affect their BP control.
Comorbid conditions, whose prevalence varies by race/ethnicity, can also affect BP control and thus are important to account for.
We suggest an enhanced model of factors leading to disparities in BP control.
We identified all white and black patients ages 21 and older with 3 separate outpatient diagnoses of hypertension in 2004 in the primary care practices of a northeastern academically affiliated urban safety net tertiary care hospital. We use the term “black” to refer to patients of African or Caribbean descent. The study was approved by the institutional review board, and all subjects gave informed consent.
Study staff tracked clinic visits of these 10 125 patients over 19 months (October 2004 to June 2006), and, as they presented for care, approached 3526 of them to request study participation. Those willing were asked a series of questions and administered a 6-item cognitive screen to determine eligibility.13 However, 654 patients (19% of 3526) overtly refused to participate and 920 patients (26% of 3526) responded that they were unable to participate that day but were potentially willing in the future, all before we were able to assess their eligibility. Subsequently, 1083 patients (55% of the remaining 1952) were excluded for reasons including cognitive difficulties, hearing impairment, not speaking English, or not being prescribed antihypertensive medications; we enrolled 869 patients. We then applied this 55% exclusion rate to the 1574 nonrespondents whose eligibility we had been unable to assess (654 refusers and 920 with no time) and estimated that 708 (45%) probably would have been eligible. Thus, we calculated our participation rate as participants/participants+likely eligible subjects (869/869+708=55%). We subsequently excluded 63 additional patients for whom study staff were unable to obtain BPs, for a final sample of 806 (Figure 1).
We evaluated the representativeness of the enrolled cohort, compared with those eligible to be enrolled, using the limited data available on the nonenrolled patients. Enrolled patients were more likely to be white (43% versus 32%, P<0.0001) and were younger (mean age, 59 versus 65 for nonenrolled patients, P<0.0001), but there was no difference in sex distribution from the parent population of eligible patients (not shown).
Sociodemographic Characteristics and Medical History
Patient sociodemographic characteristics including race (assessed using US Census categories), education, and income were obtained through self-report. To assess patient literacy, we used the REALM-Short Form.14 We used 5 separate dichotomous (yes/no) questions to assess insurance status, asking if patients currently have health insurance coverage through Medicare, Medicaid, Medigap, Free Care, or other insurance.
Patient clinical data were extracted from the electronic medical record, including age, sex, height, weight, and hypertension diagnosis. The electronic medical record was searched to obtain diagnoses of comorbid conditions including renal insufficiency, coronary artery disease, peripheral vascular disease, nicotine dependence, hyperlipidemia, diabetes mellitus, congestive heart failure, cerebrovascular disease, and obesity, because these conditions may influence the management of hypertension.15 Obesity was considered a current diagnosis for any patient with an electronic medical record diagnosis or a calculated body mass index of at least 30.
Health Beliefs and Illness Perception
We examined a broad spectrum of patient beliefs and perceptions about high BP and related medications. We used the “Beliefs about Medicines Questionnaire”; 10 items assess patient concerns about present and potential future adverse effects from their medications and 8 items measure patients’ beliefs regarding the necessity of their medications; we edited the items to relate responses specifically to BP medicines16,17 (items scored on a 5-point scale: strongly agree to strongly disagree). Scores were summed within each scale to create an overall scale score (range, 8 to 40 for the “necessity” scale, Cronbach α=0.81; 10 to 50 for the “concerns” scale, α=0.80). Each score was divided by the number of items to obtain a mean summary score (range, 1 to 5); higher numbers indicated either greater concerns about medications or greater beliefs in their necessity.
We used 4 additional items from our prior work18 to evaluate the degree of seriousness with which patients perceive hypertension, asking “How serious do you think high BP is, in general?”; “How serious do you think your high BP is, given your current use of medication?”; “If you did not take your BP medications, how likely do you think it would be that your BP would get worse over the next year?”; and “If you did not take your BP medications, how likely do you think it is that you would develop other health problems over the next year?” (all scored on a scale of 1 to 5: extremely serious to not at all serious for the former 2 questions; very likely to very unlikely for the latter 2). We also included 10 individual items from the “cause” dimension of the “Illness Perception Questionnaire” to assess illness identity, cause, timeline, consequences, and cure control to examine patients’ subjective beliefs about the etiology of their high BP (responses on a 5-point scale; range, strongly agree to strongly disagree).19
Perceived Discrimination in Health Care
We included 3 measures to assess patient perceptions of race-based discrimination in the health care setting. We used 5 questions that were a subset of the Commonwealth Fund 2001 Health Care Quality survey, focusing specifically on the patient perception of his/her provider and of encountering discrimination while receiving medical care, in general.20 We created an additional question about the patient’s perception of his/her provider’s understanding of the patient’s cultural background and how it affects his/her health; each item was examined individually. We also included 7 dichotomous items from a measure of patient perceptions of discrimination in accessing health care,21 counting the number of experiences reported and creating a continuous variable (higher score indicates more experiences of discrimination21; α=0.90).
Medication Adherence and Hypertension Management
To assess medication adherence, we used the Hill-Bone Compliance to High Blood Pressure Therapy Scale, comprising items scored on a 4-point scale (“none of the time” to “all of the time”).22 We included the 9-item adherence subscale, which has been validated against BP control, summing the items to create a scale score (range, 9 to 36; higher scores indicate less adherence; α=0.74).
Outcome Assessment: BP Control
Research staff assessed patient BP using an automatic, portable machine (Omron HEM-907, Bannockburn, Ill), which was validated according to the international validation protocol and deemed an appropriate instrument for accurate BP measurement.23 We excluded the 7% of patients without a BP reading from study staff. We dichotomized the BP readings to indicate whether each patients’ BP was controlled or not, for example, when their systolic BP exceeded 140 mm Hg or their diastolic BP exceeded 90 mm Hg, according to the Joint National Committee on Hypertension 7 standards at the time of the study, which also specified that for patients with diabetes or renal insufficiency, BP should not exceed 130/80 mm Hg.15
We first examined bivariate associations between race and each of the sociodemographic, clinical, attitudinal, experiential, and medication adherence variables, using χ2 or t tests, as appropriate. Next, we performed bivariate analyses to determine whether this same set of variables was associated with BP control (yes/no). Finally, BP control was modeled as a function of the covariates using random-effects logistic regression. The random effects, which were assumed to be mean-zero gaussian additive errors on the logit scale, accounted for 2 levels of clustering: patients within providers and providers within clinics.
We fit 6 sets of models of increasing numbers of covariates, including only patients with complete data. In the first, we examined the effects of race alone on BP control. Next, we examined the effects of race on BP control, adjusting for age and other sociodemographic characteristics. The third model added medication adherence, the fourth added health beliefs, the fifth added experiences of discrimination, and the sixth added comorbid conditions. Within each model, we chose the subset of additional variables through an ordinary logistic regression stepwise selection procedure, forcing in provider indicators as fixed effects, keeping significant variables from the prior model, and including race in all models. This procedure prevents collinearity and overparameterization. We used a probability value of 0.05 for variables to enter or be removed from the model. c-Statistics and Hosmer-Lemeshow analyses were performed on the models resulting from the stepwise procedure. Each model was then rerun with the random effects terms. All analyses were conducted using SAS 9.1.3 (SAS Institute, Cary, NC) with the exception of the random-effects logistic regression, which was conducted using the statistics package R (version 2.8.024).
Sociodemographic Characteristics of the Sample
Most of the sample were black (57%) or female (65%), with an overall mean age of 59 years. White patients were older (61 versus 58 years), and more likely to have at least a high school education (90% versus 71%). Black patients were more likely to have insurance coverage through Medicaid or Free Care (42% versus 22%, 41% versus 25%, respectively), whereas white patients were more likely to have “other” (private) insurance (59% versus 35%). There were race differences in combined household family income, with a greater percentage of blacks earning low incomes of <$20 000 (58% versus 36% whites) and being less likely to have a literacy score of 9th grade or higher (48% versus 84%), (all P<0.001; Table 1⇓).
BP and Medical History by Race
A greater percentage of white patients had controlled BP (65% versus 53%), with lower systolic and diastolic BP than blacks (white systolic BP, 130 mm Hg versus 132 mm Hg; white diastolic BP 76 mm Hg versus 81 mm Hg). White patients were more likely to have hyperlipidemia (60% versus 47%), peripheral vascular disease (7% versus 4%), benign prostatic hypertrophy (6% versus 2%), coronary artery disease (19% versus 8%), and cerebrovascular disease (7% versus 4%). Black patients were more likely to have diabetes (40% versus 24%), renal insufficiency (7% versus 4%), congestive heart failure (5% versus 1%), and to be obese (65% versus 52%, all P<0.05).
Health Beliefs and Illness Perceptions
Blacks had significantly more concerns about their BP medications than whites (2.5 versus 2.1, P<0.0001). White patients were significantly more likely to respond that their BP was less serious, given their current use of medications (3.3 versus 2.8, P<0.0001).
When asked about the causality of high BP, blacks agreed more with the notion that it is caused by a germ or virus or that diet, pollution, or heredity played a major role in causing BP (Table 1⇑). Blacks were more likely to indicate that it was just by chance that they became ill with hypertension, that other people played a large role in causing their BP, or that high BP was caused by poor medical care in the past.
When asked if there was ever a time they would have gotten better medical care if they belonged to a different race or ethnic group or if they ever felt that a doctor or medical staff judged them unfairly or treated them with disrespect because of how well they spoke English, blacks were more likely to respond “yes” than whites (19% versus 1% and 4% versus 0%, respectively). Although all patients generally agreed that their provider understood their background and values, black patients agreed less strongly (1.5 versus 1.4), and though all patients disagreed that their provider looks down on them and the way they live their life, white patients disagreed more strongly (4.5 versus 4.3). Blacks reported more experiences of discrimination when receiving health care than did whites (1.1 versus 0.2, all P<0.05).
White patients reported better medication adherence than did black patients (9.9 versus 11.0, P<0.0001).
Covariates by BP Control
A greater proportion of patients with controlled BP were white compared with patients with uncontrolled BP (48% versus 36%). Patients with uncontrolled BP were more likely to have a household income of <$20 000 (56% versus 43%), were more likely to have Medicaid (40% versus 29%), and were less likely to have “other” insurance (38% versus 51%). Patients with uncontrolled BP were more likely to have diabetes (45% versus 25%) and renal insufficiency (10% versus 3%) and concerns about their BP medications (2.4 versus 2.3). Patients with controlled BP were more likely to disagree that their own BP was serious, given their current use of medication (3.1 versus 2.9), and reported better medication adherence (10.4 versus 10.7, all P<0.05).
The first model, only adjusted for race, accounting for physician and clinic, indicated that white patients had higher odds of having controlled BP than blacks (model 1, b=0.42, P=0.0068; Table 2; c-statistic (c)=0.661; Hosmer and Lemeshow goodness-of-fit test [HL] P=0.4226). The effect of race on BP control persisted in the second model, after adjustment for income (other sociodemographic variables were excluded through the ordinary logistic regression stepwise procedure). The third model added a measure of adherence, which was not significantly related to BP control, so these 2 latter models had the same results, with race continuing to be a significant predictor of BP control (models 2 and 3, b=0.37, P=0.0238; model 2, c=0.691, HL P=0.7127; model 3, c=0.670, HL P=0.9260). In the fourth model, an item assessing patients’ beliefs that high BP is largely due to one’s own behavior was added, as well as 2 items assessing the degree of seriousness with which patients perceive hypertension (all other attitudinal and experiential factors were excluded through the stepwise procedure). In this model, race was no longer significantly associated with odds of BP control (model 4, b=0.33, P=0.0531, c=0.713, HL P=0.3932).
In the fifth model, 1 item assessing experiences with perceived discrimination in health care was added, specifically, perceptions about whether they would have ever gotten better medical care if they belonged to a different race or ethnic group (other items assessing discrimination were excluded through the stepwise procedure). Race was significant in this model (model 5, b=0.48, P=0.0074, c=0.708, HL P=0.8660).
In the final model, diabetes, renal insufficiency, and benign prostatic hypertrophy were added (other comorbid conditions were excluded during the stepwise procedure in SAS). Here, race was no longer a significant predictor of BP control (model 6, b=0.32, P=0.0876, c=0.740, HL P=0.4274).
Understanding and ameliorating racial disparities in BP control is a major public health and clinical concern. We hypothesized that after adjusting for an extensive set of potential confounders, race would no longer be significantly associated with BP control, and the results generally supported this notion. Although the effects of race persisted after accounting for sociodemographic factors, the inclusion of BP-related attitudes and beliefs rendered race insignificant. However, the introduction of the discrimination variables made race significant again, in a counterintuitive fashion, although in the final model, with the inclusion of comorbid conditions, race was no longer significant. The finding that patients who agreed with the statement that there was “ever a time when they would have gotten better medical care if they had belonged to a different race/ethnic group” had better BP control is puzzling. We carefully explored this dynamic, ruling out the possibility that race-discrimination interactions were driving it, and finding that even if we removed this variable, another discrimination variable became significant in the same counterintuitive direction (not shown). The variable was limited by its reference point (eg, was there ever a time …), so it is possible that patients who felt they were getting bad care in the past had changed clinicians and are now getting good care, leading to better current BP care and control. It is also possible that another, unmeasured, confounder caused these results.
The study findings are different than the Bosworth study,11 which indicated that after controlling for a similar range of factors (not including discrimination or comorbid conditions), race remained a significant predictor of BP control, among VA patients in one Southern city. They speculated that the results they obtained in that setting, where access to care is assured, might be different than those found elsewhere, and our results in a northeastern urban safety net hospital setting support this notion. Several other studies also controlled for subsets of the factors we included here, but race remained significant.6,25,26 Thus, although our findings support Bosworth’s proposed framework as a descriptive model, and the notion that numerous psychosocial, behavioral, and experiential factors mediate the relationship between race and BP control,11 they indicate that comorbid conditions, whose prevalence varies by race/ethnicity, are also important to account for in models of disparities in BP control.
Several findings have clinical implications. Blacks reported more experiences of discrimination, and such experiences may erode overall trust in physicians, their diagnoses, and the therapies they prescribe. Experiences of discrimination in the community setting are generally associated with higher BP27,29,30 with less use of chronic disease care28 and may negatively affect patients’ acceptance of their diagnosis and beliefs in the necessity of or concerns about the associated therapy, which are foundational to patient adherence to prescribed medications.29 Unequal treatment, documented by us and others,30,31 may also contribute to disparities in BP outcomes.
Blacks indicated worse medication adherence and more concerns about BP. Each of these is potentially ameliorable through educational or counseling interventions, and our results suggest that addressing these will help address disparities in BP control.
This study was limited by its focus on patients in a single setting and its inclusion of only black (albeit both African-American and Caribbean-born) and white patients. Although we required that participants have 3 separate outpatient diagnoses of hypertension, our inability to contact or enroll many eligible patients may have biased our sample toward more frequent users. The observational nature of these data limits our ability to form causal inferences because we were not able to randomize by attitudinal characteristics or ascertain that certain attitudes or experiences preceded BP outcomes in time. Further, our measure of adherence, although internally consistent and previously validated against BP control, was obtained by self-report. However, the large sample, which included women and detailed assessments of the richest array of putative factors examined to date, offsets the limitations.
Among the potential causes of disparities in BP control, the etiologic factors could arise from the patient (health beliefs and experiences, medication adherence or self-care behaviors, clinical or biological factors), the provider (practice style, communication skills, attitudes), the doctor-patient interaction, or the environment. Although the Bosworth model provided an excellent summary of the psychosocial and cultural factors that might be associated with BP control, we propose that a model for racial disparities in BP control should include a wider array of factors and include hypothesized associations (Figure 2). The present results help to demonstrate the effects of a variety of factors on race differences in BP, but we lacked data on other self-care behaviors important to hypertension management (eg, diet, exercise) to fully address this question. Nor are we able to rule out biological differences, such as race-linked nitric oxide deficiencies associated with cardiovascular disease32 or differences in the process of care. Our future work will also examine the effects of racial differences in providers’ therapeutic intensification, which varies by race,33 on BP outcomes. Similar to our prior suggestions for future directions in research on racial differences in invasive cardiac procedure use,31 here we propose additional careful attention by clinicians, researchers, and, ultimately, policymakers, to a comprehensive array of factors associated with race to identify and intervene on the causes of racial disparities in BP outcomes.
We thank Peter Davidson, MD, and the clinic and research staff for their assistance.
Sources of Funding
This study was supported by NIH/National Heart, Lung, and Blood Institute grant R01 HL072814 (Dr Kressin, PI); Dr Kressin is also supported by a Research Career Scientist award (RCS 02-066-1) from the Health Services Research and Development Service, Department of Veterans Affairs.
The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.
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