# Racial/Ethnic Variability in Hypertension Prevalence and Risk Factors in National Health Interview Survey

Authors: L. Holmes; J. Hossain; D. Ward; F. Opara
Journal: ISRN Hypertension
 (2013)

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## Abstract

Objective. Hypertension is one of the leading causes of death attributed to cardiovascular diseases, and the prevalence varies across racial/ethnic groups, with African Americans being disproportionately affected. The underlying causes of these disparities are not fully understood despite volume of literature in this perspective. We aimed in this current study to examine ethnic/racial disparities in hypertension utilizing Hispanics as the base racial/ethnic group for comparison. Research Design and Methods. We utilized the National Health Interview Survey (NHIS), which is a large cross-sectional survey of the United States non-institutionalized residents to investigate the racial/ethnic disparities in hypertension after the adjustment of other socio-economic, demographic, and prognostic risk factors. The study participants were adults (n = 30,852). Data were analyzed using Chi square statistic, and logistic regression model. Results. There were statistically significant differences by race/ethnicity with respect to income, education, marital status, smoking, alcohol, physical activities, body mass index, and age, P < 0.01, but not insurance coverage, P > 0.01. Hispanic ethnicity (18.9%) compared to either non-Hispanic white (27.7%) or non-Hispanic black (35.5%) was associated with the lowest prevalence of hypertension. Race/ethnicity was a single independent predictor of hypertension, with non-Hispanic black more likely to be hypertensive compare with Hispanic, prevalence odds ratio (POR), 2.38, 99% Confidence Interval (CI), 2.17–2.61 and non-Hispanic white, POR, 1.64, 99% CI, 1.52–1.77. After controlling for the confounding variables, the racial/ethnic differences in hypertension persisted. Conclusions. Racial/ethnic disparities in hypertension persisted after controlling for potential predictors of hypertension in NHIS, implying the inability of known hypertension risk factors to account for racial/ethnic variability in hypertension in US.


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## Body

## 1. Introduction

Hypertension remains one of the leading causes of cardiovascular mortality in the United States population, affecting disproportionately non-Hispanic blacks [1–4]. The etiology of hypertension is multifactorial and incidence, prevalence and mortality vary by race/ethnicity [5–7]. A study has shown that the age-adjusted prevalence of hypertension by race, in the year 2003-2004, among the United States residents of age 20 years or older was 39.1% non-Hispanic Black, 28.5% non-Hispanic White, and 27.8% Hispanic, while age-unadjusted prevalence rate was 34.4%, 30.3%, and 16.9% for three racial groups, respectively [8]. However, it is not fully understood whether the observed variance is due to race or other factors associated with race or hypertensive risk factors per se.Explanatory factors for racial/ethnic differences in hypertension include racial/ethnic differences in family income, education and insurance status. Other predictors of hypertension include socioeconomic, demographic, and prognostic factors [9–11]. Because there are racial/ethnic differences in the distribution of the postulated risk factors in hypertension, these factors may very well explain the ethnic/racial variations in hypertension prevalence in our population.This present study was conducted to examine the racial/ethnic disparities in hypertension, using the National Health Interview Survey (NHIS) data, and to determine whether or not the observed variance could be explained by the racial/ethnic disparities in the utilization of insurance coverage, income, education, and other socio-economic parameters that constantly define racial/ethnic group in the US. We hypothesized that the racial/ethnic disparities in hypertension may be explained by ethnic and racial variance in income, insurance status and related socio-economic, demographic, and prognostic factors.


## 2. Materials and Methods

This research utilized secondary data to examine the relationship between the outcome variable hypertension (HTN) and main predictor variable race/ethnicity, as well as factors known to predispose to high blood pressure (HBP), namely, family income, insurance status and other sociodemographic and prognostic variables age, sex, education level, employment status, marital status, body mass index (BMI), cigarette smoking, physical activity, and alcohol drinking status.


### 2.1. Study Population

The sample of the NHIS, 2003 consisted of 30,852 adults. Participants were non-Hispanic whites,n=20,169 (65.37%), non-Hispanic blacks, n=4,168 (13.51%), Hispanics n=5,416 (17.55%), and others, n=1,099 (3.56%). Participants were either male, n=13,427 (43.52%) or female, n=17,425 (56.48%), ages 18 years and older.


### 2.2. Data Collection and Sampling Techniques

#### 2.2.1. Data Collection Procedures

Data were collected via a personal household interview by Census interviewers. The details of the sampling are published elsewhere [12].


### 2.3. Study Variables

#### 2.3.1. Outcome Variable

The outcome variable hypertension was measured as a self-reported variable and was dichotomized as “yes” and “no.” Subjects were asked if they were ever told by their health care provider of having hypertension.


#### 2.3.2. Main Predictor (Explanatory) Variable

The main predictor variable for this study is race.  The variable race was categorized into non-Hispanic whites, non-Hispanic blacks, Hispanics, and others.


#### 2.3.3.  Other Potential Explanatory Variables

Insurance coverage was measured by any family members having insurance coverage and was categorized into “yes,” “no,” “refused,” “not ascertained,” and “do not know.” The responses “refused,” “not ascertained,” and “do not know,” because of the small numbers, were not included in the analysis. Income is measured by family income greater than $20,000 and less than $20,000. This variable was categorized into “greater than $20,000,” “less than $20,000,” “refused,” “not ascertained,” and “do not know.” The responses “refused,” “not ascertained,” and “do not know” were not included in the analysis.The socio-demographic variables are age, sex, education level, employment status, and marital status. The age of participants was originally measured as a continuous variable and later categorized into a binary scale (≥50 years versus <50 year) variable given that clinical relevance of age in the predisposition to hypertension. Both males and females were eligible for the survey provided the age requirement was satisfied. Education level was measured by the years of school attainment. This variable was collected as categorical but was recoded for suitable categories in comparing “less or equal to high school,” “some college,” and “greater than,” or equal to a bachelor’s degree. Employment status was measured by a categorical variable that elicited information on job profile. This variable was recoded in order to examine unemployment versus employment, with respect to racial distribution and the association with the outcome variables. Marital status was measured by a categorical variable and was used to examine the influence of social support system on the outcome variable hypertension.


#### 2.3.4. Prognostic Variables

Body mass index (BMI) is conceptualized by relationship between height and weight. This variable was collected on a continuous scale and was recoded into four distinct categories to reflect normal BMI and overweight BMI, utilizing the Centers for Disease Control and Prevention’s cut-off points for BMI. Smoking is conceptualized as a historical variable. This variable was collected as categorical with the main variable eliciting information on “ever smoked” and “never smoked.” The responses “refused,” “not ascertained”, and “do not know” were not included in the analysis. This variable was recoded into a binary variable. Physical activity is measured by frequency of exercise. This variable is categorized into ten groups with major categories including “never exercise,” “exercise” and “unable to exercise.” This variable was recoded into “ever exercise” (including daily, weekly, monthly, and yearly basis), versus “never exercise” (including unable to exercise), in order to examine the outcome variables and the association with race. Alcohol drinking status is collected as a categorical variable and is measured by the number of drinks within a period of time. This variable was recoded into “lifetime abstainer,” “former drinker,” and “current drinker.” This variable was used as a confounding and controlled for in association between race and hypertension.


### 2.4. Statistical Analyses

Categorical variables were described using frequency and percentages, while continuous variables were summarized using mean and standard deviation. Pearson Chi-Square statistic was used to examine racial/ethnic differences with respect to the distribution of the outcome variable hypertension, and potential explanatory variables, namely, family income, insurance coverage, socio-economic factors and other prognostic factors. The association between the main predictor variable race/ethnicity, and hypertension was assessed using unconditional univariable logistic regression model. In addition, multivariable logistic regression model was used to simultaneously adjust for the mixing effects of the potential confounding variables on the association between race and hypertension.We entered into this model age, education, marital status, sex, body mass index, family income, physical activities, alcohol, and smoking. To enter into the multivariable model, a variable must have been significant at P<0.25 or P<0.10 for an interaction term. Further, variables with biological or clinical relevance such as age and sex were entered into the multivariable model. All analyses were two-tailed at 0.01 significance level (1% type I error tolerance). The analyses were performed using STATA statistical software version 11.0 (STATA Incorporation, College Station, Texas).


## 2.1. Study Population

The sample of the NHIS, 2003 consisted of 30,852 adults. Participants were non-Hispanic whites,n=20,169 (65.37%), non-Hispanic blacks, n=4,168 (13.51%), Hispanics n=5,416 (17.55%), and others, n=1,099 (3.56%). Participants were either male, n=13,427 (43.52%) or female, n=17,425 (56.48%), ages 18 years and older.


## 2.2. Data Collection and Sampling Techniques

### 2.2.1. Data Collection Procedures

Data were collected via a personal household interview by Census interviewers. The details of the sampling are published elsewhere [12].


## 2.2.1. Data Collection Procedures

Data were collected via a personal household interview by Census interviewers. The details of the sampling are published elsewhere [12].


## 2.3. Study Variables

### 2.3.1. Outcome Variable

The outcome variable hypertension was measured as a self-reported variable and was dichotomized as “yes” and “no.” Subjects were asked if they were ever told by their health care provider of having hypertension.


### 2.3.2. Main Predictor (Explanatory) Variable

The main predictor variable for this study is race.  The variable race was categorized into non-Hispanic whites, non-Hispanic blacks, Hispanics, and others.


### 2.3.3.  Other Potential Explanatory Variables

Insurance coverage was measured by any family members having insurance coverage and was categorized into “yes,” “no,” “refused,” “not ascertained,” and “do not know.” The responses “refused,” “not ascertained,” and “do not know,” because of the small numbers, were not included in the analysis. Income is measured by family income greater than $20,000 and less than $20,000. This variable was categorized into “greater than $20,000,” “less than $20,000,” “refused,” “not ascertained,” and “do not know.” The responses “refused,” “not ascertained,” and “do not know” were not included in the analysis.The socio-demographic variables are age, sex, education level, employment status, and marital status. The age of participants was originally measured as a continuous variable and later categorized into a binary scale (≥50 years versus <50 year) variable given that clinical relevance of age in the predisposition to hypertension. Both males and females were eligible for the survey provided the age requirement was satisfied. Education level was measured by the years of school attainment. This variable was collected as categorical but was recoded for suitable categories in comparing “less or equal to high school,” “some college,” and “greater than,” or equal to a bachelor’s degree. Employment status was measured by a categorical variable that elicited information on job profile. This variable was recoded in order to examine unemployment versus employment, with respect to racial distribution and the association with the outcome variables. Marital status was measured by a categorical variable and was used to examine the influence of social support system on the outcome variable hypertension.


### 2.3.4. Prognostic Variables

Body mass index (BMI) is conceptualized by relationship between height and weight. This variable was collected on a continuous scale and was recoded into four distinct categories to reflect normal BMI and overweight BMI, utilizing the Centers for Disease Control and Prevention’s cut-off points for BMI. Smoking is conceptualized as a historical variable. This variable was collected as categorical with the main variable eliciting information on “ever smoked” and “never smoked.” The responses “refused,” “not ascertained”, and “do not know” were not included in the analysis. This variable was recoded into a binary variable. Physical activity is measured by frequency of exercise. This variable is categorized into ten groups with major categories including “never exercise,” “exercise” and “unable to exercise.” This variable was recoded into “ever exercise” (including daily, weekly, monthly, and yearly basis), versus “never exercise” (including unable to exercise), in order to examine the outcome variables and the association with race. Alcohol drinking status is collected as a categorical variable and is measured by the number of drinks within a period of time. This variable was recoded into “lifetime abstainer,” “former drinker,” and “current drinker.” This variable was used as a confounding and controlled for in association between race and hypertension.


## 2.3.1. Outcome Variable

The outcome variable hypertension was measured as a self-reported variable and was dichotomized as “yes” and “no.” Subjects were asked if they were ever told by their health care provider of having hypertension.


## 2.3.2. Main Predictor (Explanatory) Variable

The main predictor variable for this study is race.  The variable race was categorized into non-Hispanic whites, non-Hispanic blacks, Hispanics, and others.


## 2.3.3.  Other Potential Explanatory Variables

Insurance coverage was measured by any family members having insurance coverage and was categorized into “yes,” “no,” “refused,” “not ascertained,” and “do not know.” The responses “refused,” “not ascertained,” and “do not know,” because of the small numbers, were not included in the analysis. Income is measured by family income greater than $20,000 and less than $20,000. This variable was categorized into “greater than $20,000,” “less than $20,000,” “refused,” “not ascertained,” and “do not know.” The responses “refused,” “not ascertained,” and “do not know” were not included in the analysis.The socio-demographic variables are age, sex, education level, employment status, and marital status. The age of participants was originally measured as a continuous variable and later categorized into a binary scale (≥50 years versus <50 year) variable given that clinical relevance of age in the predisposition to hypertension. Both males and females were eligible for the survey provided the age requirement was satisfied. Education level was measured by the years of school attainment. This variable was collected as categorical but was recoded for suitable categories in comparing “less or equal to high school,” “some college,” and “greater than,” or equal to a bachelor’s degree. Employment status was measured by a categorical variable that elicited information on job profile. This variable was recoded in order to examine unemployment versus employment, with respect to racial distribution and the association with the outcome variables. Marital status was measured by a categorical variable and was used to examine the influence of social support system on the outcome variable hypertension.


## 2.3.4. Prognostic Variables

Body mass index (BMI) is conceptualized by relationship between height and weight. This variable was collected on a continuous scale and was recoded into four distinct categories to reflect normal BMI and overweight BMI, utilizing the Centers for Disease Control and Prevention’s cut-off points for BMI. Smoking is conceptualized as a historical variable. This variable was collected as categorical with the main variable eliciting information on “ever smoked” and “never smoked.” The responses “refused,” “not ascertained”, and “do not know” were not included in the analysis. This variable was recoded into a binary variable. Physical activity is measured by frequency of exercise. This variable is categorized into ten groups with major categories including “never exercise,” “exercise” and “unable to exercise.” This variable was recoded into “ever exercise” (including daily, weekly, monthly, and yearly basis), versus “never exercise” (including unable to exercise), in order to examine the outcome variables and the association with race. Alcohol drinking status is collected as a categorical variable and is measured by the number of drinks within a period of time. This variable was recoded into “lifetime abstainer,” “former drinker,” and “current drinker.” This variable was used as a confounding and controlled for in association between race and hypertension.


## 2.4. Statistical Analyses

Categorical variables were described using frequency and percentages, while continuous variables were summarized using mean and standard deviation. Pearson Chi-Square statistic was used to examine racial/ethnic differences with respect to the distribution of the outcome variable hypertension, and potential explanatory variables, namely, family income, insurance coverage, socio-economic factors and other prognostic factors. The association between the main predictor variable race/ethnicity, and hypertension was assessed using unconditional univariable logistic regression model. In addition, multivariable logistic regression model was used to simultaneously adjust for the mixing effects of the potential confounding variables on the association between race and hypertension.We entered into this model age, education, marital status, sex, body mass index, family income, physical activities, alcohol, and smoking. To enter into the multivariable model, a variable must have been significant at P<0.25 or P<0.10 for an interaction term. Further, variables with biological or clinical relevance such as age and sex were entered into the multivariable model. All analyses were two-tailed at 0.01 significance level (1% type I error tolerance). The analyses were performed using STATA statistical software version 11.0 (STATA Incorporation, College Station, Texas).


## 3. Results

There were30,852,in which less than 4% were others, implying other racial/ethnic group in the United States population besides Caucasian (non-Hispanic White), African American (non-Hispanic Black), and Hispanic. The majority of the study participants were non-Hispanic whites,n=20,169 (65.4%). The remaining racial/ethnic groups were non-Hispanic blacks,n=4,168 (13.5%), and Hispanics, n=5,416 (17.5%).Table1 presents the study characteristics by race/ethnicity. There were statistically significant racial/ethnic differences with respect to education, family income, marital status, current smoking status, history of alcohol use, physical activity, body mass index (BMI), and age group, P<0.01. In contrast, there was no statistically significant racial/ethnic differences in insurance status, P>0.01. Compared to non-Hispanic whites, non-Hispanic blacks and Hispanics were less likely to acquire undergraduate and graduate degrees, (26.8%) versus (15.2% and 9.6%), respectively. Family income was significantly higher among non-Hispanic whites (72.5%) compared with non-Hispanic blacks (55.1%) and Hispanics (57.7%). In addition, Hispanics (31.1%) were less likely to smoke compared to non-Hispanic blacks (37.7%) and non-Hispanic whites (47.9%). Non-Hispanic whites (65.8%) were more likely to report of alcohol use compared to non-Hispanic blacks (49.3%) and Hispanics (51.1%). Further, Hispanics (20.1%) were less likely to exercise compared with non-Hispanic blacks (24.6%) and non-Hispanic whites (28.8%). Non-Hispanic whites (21.7%) were less likely to be overweight and obese compared with non-Hispanic blacks (33.5%) and Hispanics (25.1%). Furthermore, compared to non-Hispanic blacks (54.9%) and non-Hispanic whites (64.1%), Hispanics (42.3%) were less likely to be in the older age group (>50 years).Table 1
Study characteristics comparing covariates by race/ethnicity in a sample of community-based United States residents.
Variables
Caucasian
African American
Hispanic
Others
n
%
n
%
n
%
n
%
χ
2 (df)
P
Education
1800.0 (6)
<.0001
≤High  School
8,672
43.0
2,257
54.2
3,852
71.1
368
33.5
Some College
6,090
30.2
1,278
30.7
1,046
19.3
277
25.2
≥Bachelor’s degree
5,407
26.8
633
15.2
518
9.6
454
41.3
Income
772.3 (3)
<.0001
≤$20,000
5,547
27.5
1,872
44.9
2,290
42.3
301
27.4
>$20,000
14,622
72.5
2,296
55.1
3,126
57.7
798
72.6
Marital status
744.0 (3)
<.0001
Married
9,407
46.6
2,895
69.5
2,566
47.4
505
46.0
Nonmarried
10,762
53.4
1,273
30.5
2,850
52.6
594
54.0
Insurance status
4.3 (3)
0.222
Yes
18,005
89.3
3,717
89.2
4,799
88.6
996
90.6
No
2,164
10.7
451
10.8
617
11.4
103
9.4
Current smoking status
673.9 (3)
<.0001
Yes
9,666
47.9
1,572
37.7
1630
30.1
347
31.6
No
10,503
52.1
2,596
62.3
3,786
69.9
752
68.4
Alcohol history
660.5 (2)
<.0001
Yes
13,277
65.8
2,054
49.3
2,767
51.1
No
6,892
34.2
2,114
50.7
2,649
48.9
Physical activity
182.0 (3)
<.0001
Yes
5,816
28.8
1,025
24.6
1,087
20.1
323
29.4
No
14,353
71.2
3,143
75.4
4,329
79.9
776
70.6
Body mass index
575.3 (9)
<.0001
Underweight
421
2.2
47
1.2
62
1.22
53
5.1
Normal weight
7,812
40.8
1,169
29.9
1,782
35.0
588
56.0
Overweight
6,776
35.3
1,384
35.4
1,969
38.7
289
27.6
Obese
4,152
21.7
1,307
33.5
1,280
25.1
119
11.3
Age group
927.7 (3)
<.0001
≤50 years
7244
35.9
1,878
45.1
3,125
57.7
585
53.2
>50 years
12,925
64.1
2,290
54.9
2,291
42.3
514
46.8Table2 demonstrates the comparison of race/ethnicity by hypertension prevalence as well as race by blood pressure levels. There was a statistically significant difference in the prevalence of hypertension by race/ethnicity, χ2 (2, N=29,753) = 343.5, P≤0.001. Hispanics (18.9%) compared to non-Hispanic blacks (35.8%) and non-Hispanic whites (27.7%) were less likely to report of being diagnosed with hypertension. Likewise, there was a statistically significant difference in the levels of blood pressure by race/ethnicity. χ2 (8, N=29,753) = 216.7, P≤0.001. Compared with non-Hispanic whites (9.7%) and Hispanics (10.3%), non-Hispanic blacks (14.7%) were more likely to report of higher blood pressure levels. Next, Hispanics (1.5%), compared to non-Hispanic blacks (2.7%) and non-Hispanic whites (2.1%), were less likely to be in border line hypertension level.Table 2
The comparison of hypertension prevalence and blood pressure levels by race/ethnicity in a sample of community-based United States residents.
Variables
Caucasian
African American
Hispanic
n
%
n
%
n
%
χ
2
P
Hypertension
343.5
<0.0001
Yes
5,594
27.7
1,491
35.8
1,026
18.9
No
14,575
72.3
2,677
64.8
4,390
81.1
Blood pressure level
216.7
<0.0001
Not told
440
2.3
75
1.9
142
3.0
High
1,852
9.7
571
14.7
478
10.3
Normal
15,436
80.5
3,032
78.1
3,839
82.6
Low
1,036
5.4
97
2.5
123
2.6
Borderline
400
2.1
105
2.7
68
1.5
Notes and abbreviations: the significance level was <0.01 (1% type I error tolerance);χ2= Pearson Chi-Square value.Table3 shows the crude or unadjusted association between race/ethnicity and hypertension. There was a statistically significant difference in the prevalence of hypertension by race/ethnicity. Compared with Hispanics, non-Hispanic blacks were two times as likely to be hypertensive, prevalence odds ratio (POR) = 2.38, 99% Confidence Interval (CI), 2.17–2.61, while non-Hispanic whites were 64% more likely to be hypertensive, POR = 1.64, 99% CI, 1.52–1.77. Hypertension was statistically significantly associated with lower education, advanced age, higher BMI, lack of physical activities, and not being married, P<0.01. In contrast, there was no statistically significant association between hypertension and insurance status, POR = 0.97, 99% CI, 0.89–1.05. There was statistically significant increase in the prevalence of hypertension among smokers, compared with nonsmokers (27%), POR = 1.27, 99% CI, 1.21–1.34.Table 3
Unconditional univariable logistic regression model of racial/ethnic disparities in  hypertension prevalence in a large sample of community-based United States residents.
Variables
Prevalence odds ratio
99% Confidence interval
P
Race
Hispanics
1.00
Reference
Reference
Non-Hispanic Blacks
2.38
2.17–2.61
<0.0001
Non-Hispanic Whites
1.64
1.52–1.77
<0.0001
Family income
≤$20,000
1.00
Reference
Reference
>$20,000
0.67
0.64–0.71
<0.0001
Insurance status
Yes
1.00
Reference
Reference
No
0.97
0.89–1.05
0.43
Education
≤High  school
1.00
Reference
Reference
Some college
0.70
0.66–0.74
<0.0001
≥Bachelor’s degree
0.59
0.55–0.64
<0.0001
Age
≤50 years
1.00
Reference
Reference
>50 years
6.20
5.79–6.63
<0.0001
Body mass index
Underweight
1.00
Reference
Reference
Normal weight
0.98
0.78–1.22
0.85
Overweight
1.64
1.31–2.06
<0.0001
Obese
3.19
2.55–4.00
<0.0001
Smoking
No
1.00
Reference
Reference
Yes
1.27
1.21–1.34
<0.0001
Alcohol
No
1.00
Reference
Reference
Yes
0.65
0.62–0.69
<0.0001
Physical activities
No
1.00
Reference
Reference
Yes
0.69
0.65–0.73
<0.0001
Marital status
Nonmarried
1.00
Reference
Reference
Married
.85
0.81–0.90
<0.0001
Notes: the significance level was <0.01 (1% type I error tolerance).Table4 presents the multivariable analysis of the effect of race on hypertension after controlling for family income, education, age, BMI, smoking, alcohol history, physical activities, and marital status. The statistically significant association between race and hypertension persisted after controlling these variables, adjusted POR = 2.12, 99% CI, 1.90–2.35 for non-Hispanic blacks and adjusted POR = 1.64, 99% CI, 1.40–1.67, for non-Hispanic whites compared to Hispanics.Table 4
Unconditional multivariable logistic regression model of racial/ethnic disparities in hypertension prevalence in a large sample of community-based United States residents.
Variables
Prevalence odds ratio
99% Confidence interval
P
Race
Hispanics
1.00
Reference
Reference
Non-Hispanic Blacks
2.12
1.90–2.35
<0.0001
Non-Hispanic Whites
1.64
1.40–1.67
<0.0001
Family income
≤$20,000
1.00
Reference
Reference
>$20,000
0.74
0.70–0.79
<0.0001
Education
≤High  school
1.00
Reference
Reference
Some college
0.78
0.73–0.84
<0.0001
≥Bachelor’s degree
0.71
0.65–0.77
<0.0001
Age
≤50 years
1.00
Reference
Reference
>50 years
5.99
5.57–6.45
<0.0001
Body mass index
Underweight
1.00
Reference
Reference
Normal weight
1.03
0.81–1.30
0.838
Overweight
1.59
1.25–2.02
<0.0001
Obese
3.18
2.50–4.05
<0.0001
Smoking
No
1.00
Reference
Reference
Yes
1.09
1.02–1.15
0.008
Alcohol
No
1.00
Reference
Reference
Yes
0.79
0.74–0.84
<0.0001
Physical activities
No
1.00
Reference
Reference
Yes
0.96
0.89–1.03
0.226
Marital status
Nonmarried
1.00
Reference
Reference
Married
.89
0.83–0.94
<0.0001
Notes: the significance level was <0.01 (1% type I error tolerance).


## 4. Discussion

We aimed in this study to examine the prevalence of HTN by race/ethnicity in the US, and to determine whether or not health disparities in HTN could be explained by racial/ethnic distribution of the factors know to be associated with hypertension that are unequally distributed across racial/ethnic groups in the US. There are a few significant findings in this study. First, there is a significant racial/ethnic variation in the prevalence of hypertension. Second, there are racial/ethnic differences in family income, educational level, age, marital status, physical activities, body mass index, and physical activities. Third, racial/ethnic disparity in hypertension between non-Hispanic blacks and Hispanics is not explained by the differences in the socio-demographic, and prognostic factors, which are known risk factors for HBP.In the univariable model, non-Hispanic blacks had a greater risk of developing hypertension compared with Hispanics and non-Hispanic whites. These findings support previous literature with respect to race/ethnicity and hypertension in the United States [1–4]. In this sample, Hispanics presented with a higher family income level compared with non-Hispanic blacks. Education level [13–16], and family income [17], and insurance coverage are variables that have been well studied in association with hypertension. This study has shown that Hispanics compared to non-Hispanic whites were less likely to be in the higher income stratum, but, were more likely to be in the higher income stratum compared to non-Hispanic blacks. Lower income level has been associated with increased risk of hypertension and other chronic diseases [7, 9, 18–21]. However, our data failed to support this observation while comparing non-Hispanic whites to Hispanics. Whereas, lower education has been associated with increased prevalence of hypertension, our findings did not support this observation. Hispanics were less likely to have higher education compared with non-Hispanic blacks and non-Hispanic whites, but had the lowest prevalence of hypertension.We have also demonstrated that the prevalence of hypertension is associated with current smoking, alcohol, physical activity, body mass index, and age. Non-Hispanic whites were more likely to smoke compared with either non-Hispanic blacks or Hispanics. Smoking is a risk factor in hypertension as it results in the constriction of the blood vessels, increasing peripheral resistance, and hence elevating the blood pressure [22–24]. Compared with other racial/ethnic group, Hispanics were less likely to exercise. Physical activity is known to lower blood pressure and to be protective against the development of hypertension. Exercise can reduce the obstacles to the flow of blood by increasing the elasticity of the arterial lumen, thus decreasing peripheral resistance [25]. It is therefore unclear why hypertension is lower among the Hispanics given their lower level involvement in physical activities. Nonetheless, this observation is indicative of multifactorial etiology in hypertension, some which remain to be fully understood.This study has also shown that BMI varies by race and it associated with hypertension. Elevated BMI is associated with increased risk of hypertension due to the extra load placed on the myocardium because of increased cardiac contractibility, which leads to increased heart rate and stroke volume [26]. Therefore, by increasing cardiac output, the blood pressure is subject to elevation.Whereas Hispanics were more likely to be overweight compared with non-Hispanic whites, the prevalence of hypertension was lowest among Hispanics. Because hypertension increases with increase in body weight (overweight), it is difficult to use this as a single factor in contrasting the low prevalence of hypertension experienced by the Hispanics. In addition, Hypertension increases with advancing age due to development arterial plagues leading to arteriosclerosis and hence increasing peripheral resistance through the stiffening of the blood vessels [25–27]. Hispanics were more likely to be in the younger age group where hypertension is less prevalent. This may explain in part why hypertension was less prevalent among this racial/ethnic group compared with non-Hispanic whites and non-Hispanic blacks.We adjusted for variables in our dataset known to be confounding in the association between race/ethnicity and hypertension prevalence in order to offer possible explanations to the persistent racial/ethnic disparities in hypertension in the United States. Despite this adjustment, we found a statistically significant difference in hypertension prevalence by race/ethnicity, mainly between non-Hispanic blacks and Hispanic. Unlike other studies [7, 18, 21, 22], that have shown that racial/ethnic differences in hypertension prevalence between non-Hispanic blacks and non-Hispanic whites are removed by controlling for socio-demographic variables (income, occupation, and poverty level), racial difference in hypertension prevalence between non-Hispanic blacks and Hispanics persisted after controlling for these confounding variables. Hypertension was lowest among Hispanics, intermediate among non-Hispanic whites, and highest among non-Hispanic blacks. Despite the predisposing factors in hypertension such as education, BMI, physical activities observed largely among Hispanic ethnicity, hypertension prevalence was lowest among Hispanics. The observed lowest prevalence in HTN may be explained by the “Hispanic Paradox” which claims the role of family support system in buffering stress, thus decreasing blood pressure through arterial relaxation and the reduction in the catecholamine synthesis (norepinephrine, dopamine, and epinephrine) [28]. The results from this study is indicative of the persistent racial/ethnic disparities in hypertension prevalence and the factors that predispose to hypertension. Unlike some small studies that examined hypertension and cardiovascular risk factors [29–32], this study is very representative of the US population which allows for valid and reliable inference.Despite the strength of our study (large sample size and appropriate point estimation), there are some limitations. First, as a cross-sectional design, it is difficult to establish a temporal sequence, implying a clear direction on the causal pathway in the relationship between hypertension and race, as well as other explanatory variables. However, it is unlikely that temporal sequence is mismatched in the cause and effect relationship between race/ethnicity and hypertension, since race/ethnicity preceded the development of hypertension. Secondly, because we recoded variables that were originally collected as continuous (interval and ratio scale) into categorical level, we might have introduced misclassification bias into our findings. Thirdly, like in most epidemiologic studies, these findings may be influenced by unmeasured and residual confounding [33]. Finally, because we used secondary data in our assessment of the effect of race/ethnicity on hypertension and possible explanatory factors, there are well established risk factors in hypertension, namely, sodium and caloric intake that were not fitted in to our explanatory models. The fitting of these dietary factors (micro- and macro-nutrients) and dietary salt intake may very well have provided some explanation to the persistent racial/ethnic disparities in hypertension prevalence.In summary, this study has shown that non-Hispanic blacks are disproportionately affected by hypertension and that the Hispanics have the lowest prevalence of hypertension in this sample of noninstitutionalized US residents. Further, the racial/ethnic disparities in hypertension between non-Hispanic blacks and Hispanics persisted after controlling for confounders on the effect of race/ethnicity on hypertension prevalence. Thus, given the nature of our design (cross-sectional), this study recommends further prospective studies in order to examine the incidence of hypertension by race/ethnicity, while identifying and adjusting for potential confounders in the relationship between race/ethnicity and hypertension.



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*Source: 257842-2012-09-12.xml*