Abstract
Background
The association of atrial fibrillation (AF) with the severity and control of hypertension (HTN) remains unclear.
Methods
We analyzed data from the national biracial cohort of REasons for Geographic And Racial Differences in Stroke (REGARDS) study. The AF prevalence ratios were estimated and full multi-variable adjustment included demographics, risk factors, medication adherence, HTN duration and antihypertensive medication classes.
Results
Of the 30,018 study participants (8.6% with AF), 4,386 had normotension (4.3% with AF), 5,916 had prehypertension (4.3 with AF%), 12,294 had controlled HTN (11.2% with AF), 5,587 had uncontrolled HTN (8.1% with AF), 547 had controlled apparent treatment resistant hypertension (aTRH) (19.2% with AF), and 1288 had uncontrolled aTRH (15.5% with AF). Compared with normotension, the AF prevalence ratios for prehypertension, controlled HTN, uncontrolled HTN, controlled aTRH and uncontrolled aTRH groups in fully adjusted model were 1.01 (95% CI 0.84 – 1.21), 1.42 (1.18 – 1.71), 1.37 (1.14 – 1.65), 1.17 (0.86 – 1.58) and 1.42 (1.10 – 1.84) respectively (p < 0.001).
Conclusion
The prevalence of AF was similar among persons with HTN regardless of BP level and antihypertensive treatment resistance.
Keywords: Atrial fibrillation, treatment resistant hypertension, blood pressure, antihypertensive medications, beta-blockers
Introduction
Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, increases the risk of stroke, heart failure and all-cause mortality.1,2 Systemic hypertension (HTN) is a major modifiable risk factor for AF.3–8 Left ventricular diastolic dysfunction from long standing HTN leads to left atrial remodeling and dilation resulting in increased AF risk.3,4,9–11 Prehypertension, defined as systolic blood pressure (SBP) 120–139 mmHg and/or diastolic blood pressure (DBP) of 80–89 mmHg has been associated with the development of frank HTN and AF.12,13,14 Increased prevalence of prehypertension has been associated with aging and black race,15 but the impact of age, race, and gender on the association of prehypertension and AF remains unknown. Resistant HTN, an extreme phenotype of HTN, is defined as SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg on ≥ 3 antihypertensive medication classes.16 The term apparent treatment resistant HTN (aTRH) has been used in epidemiologic studies to describe cases of resistant HTN in which pseudoresistance (i.e., falsely labelled as having resistant HTN) is not reliably excluded.
Apparent TRH is further classified into controlled aTRH (SBP < 140 mmHg and DBP < 90 mmHg on ≥ 4 antihypertensive medication classes) and uncontrolled aTRH (SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg with ≥ 3 antihypertensive medication classes).17,18 In persons with HTN, the prevalence of AF has been reported to be higher among those with uncontrolled HTN compared to controlled HTN.8 Antihypertensive medications such as beta-blockers and angiotensin converting enzyme inhibitors (ACE-I) are associated with decreased AF risk.19–21 However, the prevalence of AF among hypertensive persons with treatment resistance based on the number of antihypertensive medications used and BP control remains unknown.
In this study, using data from the REasons for Geographic and Racial Disparities in Stroke (REGARDS) study, we determined the cross sectional association between AF and BP level and HTN severity (defined by the number of antihypertensive medication class used). We hypothesized that the prevalence of AF would increase with increasing HTN severity and poorer BP control; we further investigated differences in this association by age, gender, race and geographical region.
Methods
REGARDS is a longitudinal study designed to investigate factors contributing to excess stroke mortality across the southeastern United States (US) and among blacks. The details of REGARDS sample and study recruitment have been previously described.22 Briefly, the REGARDS study includes a cohort of 30,239 black and white adult’s ≥ 45 years old recruited from the 48 continental US states between January 2003 and October 2007. The study was designed to balance on gender and race, with oversampling from regions in the Southeastern US with high stroke incidence. The final cohort included 55% women, 42% blacks, and 55% in the stroke belt (defined as North Carolina, South Carolina, Georgia, Alabama, Mississippi, Arkansas, Tennessee and Louisiana). Briefly, participants were recruited via mail and telephone. Trained personnel using computer-assisted telephone interview obtained baseline demographic information and medical history. Anthropometric and BP measurements, venous blood samples, brief physical exam, electrocardiogram, and pill bottle review of medications were conducted during the in-home visit 3–4 weeks after the telephone interview. All participants provided written informed consent and the study protocol was approved by the participating Institutional Review Boards.
Blood pressure measurements
BP was taken by trained examiners using android sphygmomanometer. BP was measured twice following a standard protocol. All participants were asked to sit for 5 minutes with feet on floor prior to BP measurement, and there was a 30-second interval between measurements. The average of two readings was calculated. BP quality was monitored by central examination of digit preference and retraining of personnel as needed.
Definition of groups based on BP and antihypertensive treatment
We stratified the cohort into 6 mutually exclusive groups based on BP control and number of antihypertensive medications used. We defined normotension as SBP < 120 mmHg and DBP < 80 mmHg without antihypertensive medication use; prehypertension as SBP 120 – 139 mmHg and/or DBP 80 – 89 mmHg without antihypertensive medication use12; controlled HTN as SBP < 140 mmHg and DBP < 90 mm Hg on ≤ 3 classes of antihypertensive medications23; uncontrolled HTN as SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg on none or < 3 classes of antihypertensive medications; controlled aTRH as SBP < 140 mmHg and DBP < 90 mm Hg on ≥ 4 classes of antihypertensive medications and uncontrolled aTRH as SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg on ≥ 3 classes of antihypertensive medications.
AF ascertainment
Details of AF ascertainment in REGARDS have been previously reported.24 Briefly, baseline AF was determined using: 1) self-reported AF during computer-assisted telephone surveys based on history of physician diagnosis of AF; and 2) electrocardiogram (ECG) obtained during in-home visit that was centrally read by electrocardiographers blinded to clinical data.
Covariates
Demographics included age, race, and sex. Geographic regions of stroke prevalence (stroke belt, stroke buckle and non-belt) were also included. Measures of socioeconomic status included annual household income (< $35,000 or ≥ $35,000) and highest level of education attained (less than high school, high school completion or higher). Cardiovascular risk factors included exercise (any vs none), current smoking, heavy alcohol use (defined by National Institute on Alcohol Abuse and Alcoholism as: ≥ 7 drinks/week for women and ≥ 14 drinks/week for men),25 diabetes (fasting glucose ≥ 126mg/dl or non-fasting glucose ≥ 200mg/dl or self-reported history of diabetes mellitus or use of diabetic medications), self-reported history of coronary heart disease, stroke or transient ischemic attack, renal function as urine albumin/creatinine ≥ 30mg/g, waist circumference; serum low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), triglycerides and total cholesterol levels and high-sensitivity C-reactive protein (CRP) levels. The presence of left ventricular hypertrophy (LVH) was determined based on the ECG Cornell LVH criteria. Medication adherence was determined based on the standard Morisky Medication Adherence Score.26 HTN duration was determined based on the self-reported history of short, medium, and long-term (i.e., < 10, 10 – 20 and > 20 years respectively). Comorbidities and medication use were included as listed in Table 1.
Table 1.
Baseline characteristics of the study participants
| Blood Pressure Groups | |||||||
|---|---|---|---|---|---|---|---|
|
| |||||||
| Characteristics | Overall | Normotension | Prehypertension | Controlled HTN | Uncontrolled HTN | Controlled aTRH | Uncontrolled aTRH |
| Sample size | 30,018 | 4,386 | 5,916 | 12,294 | 5,587 | 547 | 1,288 |
| Atrial fibrillation, n (%) | 2582 (8.6) | 190 (4.3) | 257 (4.3) | 1377 (11.2) | 453 (8.1) | 105 (19.2) | 200 (15.5) |
| Age, mean ± SD | 64.9 ± 9.4 | 60.7 ± 8.9 | 62.9 ± 9.2 | 66.3 ± 9.2 | 66.1 ± 9.4 | 67.3 ± 8.5 | 67.6 ± 8.8 |
| Black, n (%) | 12430 (41.4) | 1099 (25.1) | 1948 (32.9) | 5429 (44.2) | 2829 (50.6) | 305 (55.8) | 820 (63.7) |
| Male, n (%) | 13484 (44.9) | 1652 (37.7) | 2988 (50.5) | 5258 (42.8) | 2759 (49.4) | 245 (44.8) | 582 (45.2) |
| Stroke region, n (%) | |||||||
| Non-belt | 13358 (44.5) | 1948 (44.4) | 2766 (46.8) | 5289 (43.0) | 2543 (45.5) | 233 (42.6) | 579 (45.0) |
| Belt | 10381 (34.6) | 1467 (33.4) | 1973 (33.4) | 4292 (34.9) | 2002 (35.8) | 189 (34.6) | 458 (35.6) |
| Buckle | 6279 (20.9) | 971 (22.1) | 1177 (19.9) | 2713 (22.1) | 1042 (18.7) | 125 (22.9) | 251 (19.5) |
| Annual household income, n (%) | |||||||
| ≥ $35,000 | 13598 (45.3) | 2562 (58.4) | 3137 (53.0) | 5193 (42.2) | 2096 (37.5) | 206 (37.7) | 404 (31.4) |
| < $35,000 | 12715 (42.4) | 1314 (30.0) | 2067 (34.9) | 5518 (44.9) | 2833 (50.7) | 271 (49.5) | 712 (55.3) |
| Declined to report | 3705 (12.3) | 510 (11.6) | 712 (12.0) | 1583 (12.9) | 658 (11.8) | 70 (12.8) | 172 (13.4) |
| Education less than high school, n (%) | 3771 (12.6) | 252 (5.8) | 522 (8.8) | 1705 (13.9) | 912 (16.3) | 97 (17.7) | 283 (22.0) |
| Current smoking, n (%) | 4370 (14.6) | 728 (16.7) | 845 (14.3) | 1582 (12.9) | 986 (17.7) | 75 (13.8) | 154 (12.0) |
| Any exercise, n (%) | 19387 (65.6) | 3105 (71.9) | 4238 (72.8) | 7590 (62.6) | 3449 (62.8) | 289 (53.5) | 716 (56.6) |
| Heavy alcohol use, n (%) | 1181 (4.0) | 185 (4.3) | 265 (4.6) | 418 (3.5) | 264 (4.8) | 16 (3.0) | 33 (2.6) |
| Diabetes, n (%) | 7591 (25.3) | 396 (9.0) | 763 (12.9) | 3920 (31.9) | 1595 (28.5) | 295 (53.9) | 622 (48.3) |
| History of CHD, n (%) | 5288 (17.6) | 292 (6.7) | 465 (7.9) | 2888 (23.5) | 969 (17.3) | 229 (41.9) | 445 (34.5) |
| History of stroke/TIA, n (%) | 3023 (10.1) | 167 (3.8) | 251 (4.2) | 1605 (13.1) | 628 (11.3) | 109 (20.0) | 263 (20.4) |
| Ratio of albumin to creatinine ≥ 30 mg/g, n (%) | 4353 (15.2) | 223 (5.3) | 480 (8.4) | 1797 (15.5) | 1262 (23.8) | 143 (28.4) | 448 (36.4) |
| Waist circumference, mean ± SD | 96.2 ± 15.5 | 86.9 ± 13.4 | 93.8 ± 13.7 | 97.9 ± 15.1 | 99.5 ± 15.8 | 104.4 ± 17.0 | 103.6 ± 16.8 |
| Presenceof LVH, n (%) | |||||||
| No | 19986 (66.6) | 3354 (76.5) | 4073 (68.8) | 8196 (66.7) | 3276 (58.6) | 363 (66.4) | 724 (56.2) |
| Yes | 1042 (3.5) | 36 (0.8) | 93 (1.6) | 462 (3.8) | 281 (5.0) | 37 (6.8) | 133 (10.3) |
| Not available | 8990 (29.9) | 996 (22.7) | 1750 (29.6) | 3636 (29.6) | 2030 (36.3) | 147 (26.9) | 431 (33.5) |
| Aspirin use, n (%) | 12994 (43.3) | 1250 (28.5) | 1883 (31.8) | 6409 (52.2) | 2344 (42.0) | 361 (66.1) | 747 (58.0) |
| Statin use, n (%) | 9450 (31.5) | 718 (16.4) | 1037 (17.5) | 5219 (42.5) | 1518 (27.2) | 311 (56.9) | 647 (50.2) |
| Warfarin use, n (%) | 1106 (3.7) | 51 (1.2) | 73 (1.2) | 680 (5.5) | 165 (3.0) | 61 (11.2) | 76 (5.9) |
| High-sensitivity C-reactive protein | |||||||
| (mg/L), median [25th, 75th percentiles] | 2.2 [1.0, 5.1] | 1.4 [0.7, 3.4] | 1.9 [0.8, 4.1] | 2.5 [1.1, 5.8] | 2.7 [1.1, 5.9] | 2.9 [1.3, 6.4] | 3.0 [1.3, 6.6] |
| Total Cholesterol, mean ± SD | 192.1 ± 40.1 | 197.8 ± 38.2 | 199.4 ± 38.5 | 185.8 ± 39.4 | 197.1 ± 41.8 | 172.6 ± 39.2 | 184.6 ± 39.8 |
| High-density lipoprotein cholesterol, mean ± SD | 51.8 ± 16.1 | 55.9 ± 16.9 | 52.4 ± 16.0 | 50.5 ± 15.6 | 51.9 ± 16.7 | 45.9 ± 14.1 | 49.1 ± 14.1 |
| Low-density lipoprotein cholesterol, mean ± SD | 113.9 ± 34.6 | 119.0 ± 33.4 | 121.3 ± 33.6 | 108.0 ± 33.5 | 117.7 ± 36.1 | 98.2 ± 33.6 | 107.6 ± 34.9 |
| Triglycerides | 111 [81, 158] | 97 [72, 136] | 107 [80, 153] | 115 [84, 164] | 115.5 [83, 163] | 117 [89, 176] | 118 [87, 168] |
| Anti-hypertensive medication use, n (%) | |||||||
| Beta-blockers | 6797 (22.6) | 0 (0.0) | 0 (0.0) | 4334 (35.3) | 1017 (18.2) | 530 (96.9) | 916 (71.1) |
| Calcium-channel blockers | 6179 (20.6) | 0 (0.0) | 0 (0.0) | 3717 (30.2) | 1090 (19.5) | 491 (89.8) | 881 (68.4) |
| ACEI/ARBs | 10826 (36.1) | 0 (0.0) | 0 (0.0) | 7230 (58.8) | 1890 (33.8) | 541 (98.9) | 1165 (90.5) |
| Mineralocorticoid receptor antagonists | 387 (1.3) | 0 (0.0) | 0 (0.0) | 203 (1.7) | 11 (0.2) | 106 (19.4) | 67 (5.2) |
| Diuretics | 9191 (30.6) | 0 (0.0) | 0 (0.0) | 6137 (49.9) | 1386 (24.8) | 539 (98.5) | 1129 (87.7) |
All p-values testing differences across blood pressure groups are < 0.001.
Abbreviations: HT - hypertension; aTRH - apparent treatment resistant hypertension; CHD - coronary heart disease; TIA - transischemic attack; LVH - left ventricular hypertrophy; ACEI/ARBS - angiotensin converting enzyme inhibitor/angiotensin receptor blockers; SD - standard deviation
Statistical analysis
Descriptive statistics included proportions, means and standard deviations, and medians and 25th and 75th percentiles where appropriate. Prevalence ratios (PR) for AF were calculated using Poisson regression with a robust variance estimator. Models were constructed among the 6 BP groups sequentially using an unadjusted model 1; model 2 adjusted for age, race, gender, income, education, and stroke region; model 3 adjusted for model 2 covariates and current smoking, exercise, alcohol use, diabetes mellitus, albumin-creatinine ratio, waist circumference, LVH, aspirin use, statin use, warfarin use, log-transformed CRP, and total cholesterol to HDL-C ratio; model 4 adjusted for model 3 covariates and HTN duration (short, medium and long); model 5 adjusted for model 4 and use of antihypertensive medication classes such as beta-blockers, calcium channel blockers, ACE-I/angiotensin receptor blockers, mineralocorticoid antagonists and diuretics. Additional model adjusting for model 5 and medication adherence, history of coronary heart disease (CHD), stroke or transient ischemic attack was assessed. Subgroup analyses were performed to evaluate effect modification by age (< 70 vs ≥ 70 years), race (white vs black), gender (female vs male) and geographic region (stroke belt vs non-stroke belt) Statistical significance was defined as p < 0.05 for all comparisons. SAS version V9.3 (Cary, NC) was used for all the analyses.
Results
From the overall sample of 30,183 participants, those with no data on AF, SBP or medication bottle count were excluded, resulting in a final sample size of 30,018 participants. Table 1 shows the baseline characteristics and demographics of the study cohort. The prevalence of AF was similar in the normotension and prehypertension groups. The prevalence of AF was higher in aTRH groups (controlled > uncontrolled) compared with HTN groups. The prevalence of AF in blacks, those with less than high school education, and a higher albumin-to-creatinine ratio increased across the BP groups based on increasing HTN severity and BP level.
Table 2 shows the unadjusted and adjusted prevalence of AF across BP groups with normotension as the reference group. In the unadjusted model, the prevalence of AF was higher among persons with aTRH (controlled and uncontrolled) compared to those with prehypertension, controlled HTN, and uncontrolled HTN. Among persons with aTRH, those with controlled aTRH had a higher prevalence of AF than uncontrolled aTRH. Among persons with HTN, those with controlled HTN had a higher prevalence of AF than uncontrolled HTN.
Table 2.
Prevalence ratios (95% CI) comparing atrial fibrillation across blood pressure groups.
| Blood Pressure Groups | |||||||
|---|---|---|---|---|---|---|---|
| Normotension | Prehypertension | Controlled HTN | Uncontrolled HTN | Controlled aTRH | Uncontrolled aTRH | p | |
|
|
|||||||
| Atrial fibrillation (n) | 190 | 257 | 1377 | 453 | 105 | 200 | - |
| Total (n) | 4,386 | 5,916 | 12,294 | 5,587 | 547 | 1,288 | - |
|
| |||||||
| Model 1 | 1 (ref) | 1.00 (0.83, 1.20) | 2.59 (2.23, 3.00) | 1.87 (1.59, 2.21) | 4.43 (3.55, 5.53) | 3.58 (2.97, 4.33) | <0.001 |
| Model 2 | 1 (ref) | 0.97 (0.81, 1.17) | 2.41 (2.07, 2.80) | 1.78 (1.51, 2.11) | 4.20 (3.35, 5.25) | 3.44 (2.83, 4.18) | <0.001 |
| Model 3 | 1 (ref) | 0.99 (0.83, 1.18) | 1.90 (1.63, 2.21) | 1.59 (1.35, 1.89) | 2.50 (1.98, 3.15) | 2.54 (2.08, 3.10) | <0.001 |
| Model 4 | 1 (ref) | 1.00 (0.83, 1.20) | 1.88 (1.58, 2.24) | 1.59 (1.33, 1.90) | 2.37 (1.85, 3.03) | 2.39 (1.92, 2.98) | <0.001 |
| Model 4a | |||||||
| (beta-blockers) | 1 (ref) | 1.00 (0.83, 1.20) | 1.56 (1.31, 1.86) | 1.42 (1.19, 1.71) | 1.57 (1.22, 2.03) | 1.72 (1.38, 2.16) | <0.001 |
| Model 5 | 1 (ref) | 1.01 (0.84, 1.21) | 1.42 (1.18, 1.72) | 1.37 (1.14, 1.65) | 1.17 (0.86, 1.58) | 1.42 (1.10, 1.84) | <0.001 |
Model 1 is unadjusted.
Model 2 adjusts for age, race, gender, region, income, and education.
Model 3 adjusts for Model 2 covariates + smoking, exercise, heavy alcohol use, diabetes, ACR, waist circumference, LVH, regular aspirin use, statin use, and warfarin use, log-transformed CRP, and total cholesterol : HDL-C ratio.
Model 4 adjusts for Model 3 covariates + duration of hypertension (short, medium, long, none).
Model 4a adjusts for Model 4 covariates + specified medication class.
Model 5 adjusts for Model 4 covariates + use of anti-hypertensive medications, including beta-blockers, calcium channel blockers, ACEI/ARBs, mineralocorticoid receptor antagonists, and diuretics.
Abbreviations: HTN - hypertension; aTRH - apparent treatment resistant hypertension; CHD - coronary heart disease; LVH - left ventricular hypertrophy; CRP - C reactive protein; ACEI/ARBS - angiotensin converting enzyme inhibitor/angiotensin receptor blockers; ACR – albumin to creatinine ratio; HDL-C high density lipoprotein cholesterol.
After adjusting for demographics, cardiovascular risk factors, and HTN duration in model 4, the magnitude of the differences in AF prevalence between HTN (controlled and uncontrolled) and aTRH (controlled and uncontrolled) groups attenuated. AF prevalence was similar in both the pre-HTN and normotension (reference) groups. The prevalence was also similar in controlled and uncontrolled aTRH groups (PR 2.37 and 2.39, respectively). We assessed the sequential impact of antihypertensive medications on the prevalence of AF when added one at a time to model 4 (Supplemental Table 1). Of all the antihypertensive medication classes, the use of beta-blockers (model 4a) had a substantial impact on decreasing AF prevalence, especially in the controlled and uncontrolled aTRH groups. After full adjustment (model 5), the prevalence of AF was similar in controlled HTN (PR 1.42), uncontrolled HTN (PR 1.37) and uncontrolled aTRH (PR 1.42). The prevalence of AF was lowest in controlled aTRH (PR 1.17) compared with other HTN groups, but was still higher than the normotension and prehypertension groups. AF prevalence was similar across all BP groups when adjusted for medication adherence and a history of CHD or stroke/transient ischemic attack (data not shown).
When stratified by age (< 70 years and ≥ 70 years), in an unadjusted model, AF prevalence was higher among all HTN groups, and AF prevalence was higher among aTRH groups compared with the other HTN groups. However, among persons ≥ 70 years, these differences attenuated after full adjustment (Supplemental table 2). There was no evidence of effect modification by age (Supplemental table 3).
When stratified by race in the unadjusted model among both whites and blacks, compared with normotension, the AF prevalence was higher in all HTN groups, especially aTRH. However, in blacks, these differences attenuated in the fully adjusted model. Among whites, AF prevalence was higher among HTN groups (both controlled and uncontrolled) compared to aTRH groups (Supplemental Table 4). In interaction testing, after full adjustment the AF prevalence was higher among blacks than whites in persons with aTRH (p = 0.04, Supplemental Table 3). There was no evidence of effect modification by gender or region.
Discussion
The current study shows that compared to normotension, prehypertension was not associated with increased AF prevalence. The prevalence of AF was higher in hypertensive persons compared to those without HTN, but the severity and control of HTN was not associated with AF prevalence. The combination of antihypertensive medications, and beta-blockers alone, had a significant impact on AF prevalence across all BP groups. Blacks with controlled aTRH had a higher prevalence of AF compared with whites. Gender, age and geographic region had no impact on the association of AF prevalence based on HTN severity and BP control.
In some studies, prehypertension has been associated with increased risk of incident AF,14,27,28 but the current study did not show an association between prehypertension and prevalent AF. These findings were consistent when stratified by age, race, gender, and region. One of the explanations for the current findings may be that in the current study, we did not assess the duration of prehypertension duration.
The association between HTN and AF is well-established. Long-standing HTN is associated with left ventricular hypertrophy and diastolic dysfunction and resultant left atrial remodeling.
Persistent activation of the renin angiotensin aldosterone system also contributes to left atrial hypertrophy and fibrosis resulting in left atrial remodeling.9–11 The association of AF and HTN based on both treatment resistance and BP level has not been previously investigated. Several studies have described a positive association of uncontrolled BP and AF.8,14,27,29 For example, Grundvold et al described higher AF risk among men with baseline uncontrolled SBP (≥ 140 mmHg) or DBP (≥ 80 mmHg) compared to those with controlled BP.14 Vyssoulis G et al reported increased prevalence of AF with increasing SBP in persons with essential HTN.29 But, none of the aforementioned studies have stratified hypertensive persons based on antihypertensive treatment resistance and have not taken antihypertensive medication classes into account. In the current study, we stratified persons with HTN into distinct categories based on BP level and treatment resistance. This is important, because recent studies have reported an association of aTRH with cardiovascular risk factors and adverse cardiovascular events.30,31 Since aTRH is associated with an increased risk for incident stroke,18 determining the prevalence of AF, also a major stroke risk factor, among persons with aTRH could possibly explain part of the increased risk.
The current study found a higher AF prevalence in hypertensive persons compared to those with normotension or prehypertension. However, the AF prevalence was similar among persons with HTN and aTRH regardless of BP control (i.e., ≥ 140/90 mmHg vs < 140/90 mmHg). The above findings were obtained after adjusting for demographics, cardiovascular risk factors, medication adherence, HTN duration, and number of antihypertensive medications. In contrast to the literature, we adjusted for antihypertensive medications classes, which are known to affect the risk for AF. For example, beta-blockers and ACEIs/ARBs are associated with decreased AF risk. Beta-blockers may reduce the risk for AF by attenuating the effect of sympathetic nervous system on atrial automaticity and by ameliorating left ventricular and atrial remodeling.19–21 ACEIs/ARBs inhibit the activation of renin angiotensin aldosterone system and thereby reduce left atrial dilation and fibrosis, left ventricular hypertrophy and remodeling.19,20 In this study, beta-blocker use significantly decreased the prevalence of AF across all groups, especially among those with controlled aTRH. The impact of calcium channel blockers, ACE-I/ARBs, diuretics, and mineralocorticoid antagonists on AF prevalence was not substantial. After adjusting for antihypertensive medication classes, the prevalence of AF was similar among controlled HT, uncontrolled HT, and uncontrolled aTRH, and was lowest in the controlled aTRH group. Compared to other BP groups, the use of beta-blockers was highest among the controlled aTRH group (96.9%), which could possibly explain the lower AF prevalence.
The progression from HTN to uncontrolled or controlled aTRH occurs over time. In hypertensive patients, antihypertensive medications are usually titrated gradually depending on BP response; consequently, it may take few office visits before establishing the diagnosis of treatment resistant HTN.16 One of the explanations for our findings could be that atrial remodeling process in patients with aTRH may occur in early stages of HTN,32 which may lead to AF even before establishing the diagnosis of treatment resistant HTN. Moreover, treatment with certain antihypertensive medication classes and consequent BP control may reverse atrial remodeling thereby decreasing the risk of AF.33–36 However, in the current study, we assessed prevalent AF and did not assess the duration of HTN control in persons treated for HTN. Therefore, the impact of HTN control on AF prevalence could not be reliably assessed in our study. The impact of HTN control on reversal of atrial remodeling and subsequent risk of recurrent AF warrants further investigation. The current study findings suggest that the prevalence of AF remains similar among persons with HTN regardless of BP control and treatment resistance. Thus, having treatment resistance may not identify persons with an increased AF risk.
Aging, male gender, and white race have been associated with increased AF risk,15,16,37–39 but their impact on the association of AF and HTN based on severity and BP level remains unclear. In the current study, among persons < 70 years, those with HTN had increased prevalence of AF. Interestingly, among persons ≥ 70 years, having HTN was not associated with increased AF prevalence. Given that both HTN and aging are risk factors for AF, the above findings may possibly suggest that after a certain age, HTN has no additional impact on prevalent AF. Moreover, familial causes, obesity, alcohol, sports and physical activity are associated with AF in young adults, which may partly explain increased AF prevalence among persons < 70 years.40–44 In terms of race, we found that after full adjustment blacks compared with whites with controlled aTRH had a significantly higher prevalence of AF, suggesting that racial differences persist in controlled aTRH even after adjusting for known confounding factors. These findings are in contrast to the previous studies, which showed increased prevalence of AF in whites compared with blacks; however, these studies either excluded persons with RHTN or were not stratified based on BP control and treatment resistance.37–39 The presence of racial disparities in extreme HTN phenotypes, such as aTRH, needs further investigation. In addition, among whites, the increased AF prevalence among persons with HTN compared with aTRH is probably due to the impact of medications, especially beta-blockers. The current study did not find significant differences in the association of AF prevalence and BP severity based on gender and geographical regions. The absence of gender and geographical differences in AF prevalence among more severe forms of HTN warrants further investigation.
The strengths of our study include a previously unstudied assessment of prevalent AF after adjusting for antihypertensive medication classes and based on BP level and severity; a large biracial national cohort; BP measurement and AF ascertainment by trained personnel; lower recall bias related to medication data owing to pill bottle review; adjustment for antihypertensive medication adherence and HTN duration; and assessment of AF prevalence by age, race, gender, and stroke region. Our findings should be interpreted in the context of several limitations. This was a cross-sectional analysis of baseline data; therefore, changes over time could not be assessed. We did attempt to assess the duration of prior HTN as short, medium and long-term, but the duration of preceding HTN could not be precisely obtained for each participant. AF ascertainment based on self-reported and ECG data may have potentially missed cases of paroxysmal AF. Other classes of antihypertensive medications such as vasodilators and centrally acting agents were not included in our analysis, but use of these agents was relatively uncommon and the association of these agents with AF remains unknown. The evidence of effect modification by race on AF prevalence in controlled aTRH group and lack of similar trend in other BP groups should be interpreted in context of study limitations. Due to lack of baseline data we could not assess the impact of transthoracic echocardiogram derived atrial size and duration of HTN control on atrial fibrillation prevalence. Finally, as is true with any observational study, we cannot rule out residual confounding by unmeasured covariates.
In conclusion, our study of a biracial national cohort demonstrated that prehypertension was not associated with prevalent AF. Having aTRH did not confer an increased risk of prevalent AF compared with persons without aTRH. These findings suggest a threshold effect on AF prevalence among hypertensive persons. That is, once the diagnosis of HTN is established, the risk of AF may remain the same regardless of BP level and severity. Antihypertensive medications, especially beta-blockers, significantly impact the prevalence of AF and must be taken into account when determining the association of HTN and AF. Our study emphasizes the need for continued efforts focused on HTN prevention to minimize AF risk.
Supplementary Material
Highlights.
Atrial fibrillation prevalence is not associated with prehypertension.
Atrial fibrillation prevalence is associated with hypertension.
Atrial fibrillation prevalence is not associated with treatment resistance.
Atrial fibrillation prevalence is not associated with BP control in hypertension.
Acknowledgments
This research project is supported by a cooperative agreement U01 NS041588 from the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Department of Health and Human Service. The REGARDS study was supported by NIH grant 2U01NS041588; REGARDS-MI study was supported by NIH grants R01 HL080477 and K24 HL111154. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Neurological Disorders and Stroke or the National Institutes of Health. Representatives of the funding agency have been involved in the review of the manuscript but not directly involved in the collection, management, analysis or interpretation of the data. The authors thank the other investigators, the staff, and the participants of the REGARDS study for their valuable contributions. A full list of participating REGARDS investigators and institutions may be found at http://www.regardsstudy.org. This work was also supported by funding from the National Heart, Lung, and Blood Institute, T32-HL007457.
Footnotes
Disclosure: None
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
References
- 1.Verdecchia P, Mazzotta G, Angeli F, Reboldi G. Above which blood pressure level does the risk of atrial fibrillation increase? Hypertension. 2012;59(2):184–185. doi: 10.1161/HYPERTENSIONAHA.111.187260. [DOI] [PubMed] [Google Scholar]
- 2.Camm AJ, Kirchhof P, Lip GY, Schotten U, Savelieva I, Ernst S, Van Gelder IC, Al-Attar N, Hindricks G, Prendergast B, Heidbuchel H, Alfieri O, Angelini A, Atar D, Colonna P, De Caterina R, De Sutter J, Goette A, Gorenek B, Heldal M, Hohloser SH, Kolh P, Le Heuzey JY, Ponikowski P, Rutten FH. Guidelines for the management of atrial fibrillation: the Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC) Eur Heart J. 2010;31(19):2369–2429. doi: 10.1093/eurheartj/ehq278. [DOI] [PubMed] [Google Scholar]
- 3.Andrade J, Khairy P, Dobrev D, Nattel S. The clinical profile and pathophysiology of atrial fibrillation: relationships among clinical features, epidemiology, and mechanisms. Circ Res. 2014;114(9):1453–1468. doi: 10.1161/CIRCRESAHA.114.303211. [DOI] [PubMed] [Google Scholar]
- 4.Healey JS, Connolly SJ. Atrial fibrillation: hypertension as a causative agent, risk factor for complications, and potential therapeutic target. Am J Cardiol. 2003 May 22;91(10A):9G–14G. doi: 10.1016/s0002-9149(03)00227-3. [DOI] [PubMed] [Google Scholar]
- 5.Verdecchia P, Reboldi G, Gattobigio R, Bentivoglio M, Borgioni C, Angeli F, Carluccio E, Sardone MG, Porcellati C. Atrial fibrillation in hypertension: predictors and outcome. Hypertension. 2003;41(2):218–223. doi: 10.1161/01.hyp.0000052830.02773.e4. [DOI] [PubMed] [Google Scholar]
- 6.Benjamin EJ, Levy D, Vaziri SM, D'Agostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. JAMA. 1994;271(11):840–844. [PubMed] [Google Scholar]
- 7.Psaty BM, Manolio TA, Kuller LH, Kronmal RA, Cushman M, Fried LP, White R, Furberg CD, Rautaharju PM. Incidence of and risk factors for atrial fibrillation in older adults. Circulation. 1997;96(7):2455–2461. doi: 10.1161/01.cir.96.7.2455. [DOI] [PubMed] [Google Scholar]
- 8.Thomas MC, Dublin S, Kaplan RC, Glazer NL, Lumley T, Longstreth WT, Jr, Smith NL, Psaty BM, Siscovick DS, Heckbert SR. Blood pressure control and risk of incident atrial fibrillation. Am J Hypertens. 2008;21(10):1111–1116. doi: 10.1038/ajh.2008.248. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Lau YF, Yiu KH, Siu CW, Tse HF. Hypertension and atrial fibrillation: epidemiology, pathophysiology and therapeutic implications. J Hum Hypertens. 2012;26(10):563–569. doi: 10.1038/jhh.2011.105. [DOI] [PubMed] [Google Scholar]
- 10.Burstein B, Nattel S. Atrial fibrosis: mechanisms and clinical relevance in atrial fibrillation. J Am Coll Cardiol. 2008;51(8):802–809. doi: 10.1016/j.jacc.2007.09.064. [DOI] [PubMed] [Google Scholar]
- 11.Lau DH, Mackenzie L, Kelly DJ, Psaltis PJ, Brooks AG, Worthington M, Rajendram A, Kelly DR, Zhang Y, Kuklik P, Nelson AJ, Wong CX, Worthley SG, Rao M, Faull RJ, Edwards J, Saint DA, Sanders P. Hypertension and atrial fibrillation: evidence of progressive atrial remodeling with electrostructural correlate in a conscious chronically instrumented ovine model. Hear Rhythm. 2010;7:1282–1290. doi: 10.1016/j.hrthm.2010.05.010. [DOI] [PubMed] [Google Scholar]
- 12.Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, Jr, Jones DW, Materson BJ, Oparil S, Wright JT, Jr, Roccella EJ. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: The JNC 7 Report. JAMA. 2003;289(19):2560–2571. doi: 10.1001/jama.289.19.2560. [DOI] [PubMed] [Google Scholar]
- 13.Winegarden CR. From “prehypertension” to hypertension? Additional evidence. Ann Epidemiol. 2005;15(9):720–725. doi: 10.1016/j.annepidem.2005.02.010. [DOI] [PubMed] [Google Scholar]
- 14.Grundvold I, Skretteberg PT, Liestøl K, Erikssen G, Kjeldsen SE, Arnesen H, Erikssen J, Bodegard J. Upper normal blood pressures predict incident atrial fibrillation in healthy middle-aged men: a 35-year follow-up study. Hypertension. 2012;59(2):198–204. doi: 10.1161/HYPERTENSIONAHA.111.179713. [DOI] [PubMed] [Google Scholar]
- 15.Glasser SP, Judd S, Basile J, Lackland D, Halanych J, Cushman M, Prineas R, Howard V, Howard G. Prehypertension, racial prevalence and its association with risk factors: Analysis of the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Am J Hypertens. 2011;24(2):194–199. doi: 10.1038/ajh.2010.204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Calhoun DA, Jones D, Textor S, Goff DC, Murphy TP, Toto RD, White A, Cushman WC, White W, Sica D, Ferdinand K, Giles TD, Falkner B, Carey RM. Resistant hypertension: diagnosis, evaluation, and treatment: a scientific statement from the American Heart Association Professional Education Committee of the Council for High Blood Pressure Research. Circulation. 2008;117(25):e510–526. doi: 10.1161/CIRCULATIONAHA.108.189141. [DOI] [PubMed] [Google Scholar]
- 17.Howard VJ, Tanner RM, Anderson A, Irvin MR, Calhoun DA, Lackland DT, Oparil S, Muntner P. Apparent Treatment-resistant Hypertension Among Individuals with History of Stroke or Transient Ischemic Attack. Am J Med. 2015;128(7):707–714. e2. doi: 10.1016/j.amjmed.2015.02.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Irvin MR, Booth JN, 3rd, Shimbo D, Lackland DT, Oparil S, Howard G, Safford MM, Muntner P, Calhoun DA. Apparent treatment-resistant hypertension and risk for stroke, coronary heart disease, and all-cause mortality. J Am Soc Hypertens. 2014;8(6):405–413. doi: 10.1016/j.jash.2014.03.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Marott SC, Nielsen SF, Benn M, Nordestgaard BG. Antihypertensive treatment and risk of atrial fibrillation: a nationwide study. Eur Heart J. 2014;35(18):1205–1214. doi: 10.1093/eurheartj/eht507. [DOI] [PubMed] [Google Scholar]
- 20.Manolis AJ, Rosei EA, Coca A, Cifkova R, Erdine SE, Kjeldsen S, Lip GY, Narkiewicz K, Parati G, Redon J, Schmieder R, Tsioufis C, Mancia G. Hypertension and atrial fibrillation: diagnostic approach, prevention and treatment. Position paper of the Working Group 'Hypertension Arrhythmias and Thrombosis' of the European Society of Hypertension. J Hypertens. 2012;30(2):239–252. doi: 10.1097/HJH.0b013e32834f03bf. [DOI] [PubMed] [Google Scholar]
- 21.Nasr IA, Bouzamondo A, Hulot JS, Dubourg O, Le Heuzey JY, Lechat P. Prevention of atrial fibrillation onset by beta-blocker treatment in heart failure: a meta-analysis. Eur Heart J. 2007;28(4):457–462. doi: 10.1093/eurheartj/ehl484. [DOI] [PubMed] [Google Scholar]
- 22.Howard VJ, Cushman M, Pulley L, Gomez CR, Go RC, Prineas RJ, Graham A, Moy CS, Howard G. The reasons for geographic and racial differences in stroke study: objectives and design. Neuroepidemiology. 2005;25(3):135–143. doi: 10.1159/000086678. [DOI] [PubMed] [Google Scholar]
- 23.James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, Lackland DT, LeFevre ML, MacKenzie TD, Ogedegbe O, Smith SC, Jr, Svetkey LP, Taler SJ, Townsend RR, Wright JT, Jr, Narva AS, Ortiz E. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8) JAMA. 2014;311(5):507–520. doi: 10.1001/jama.2013.284427. [DOI] [PubMed] [Google Scholar]
- 24.Soliman EZ, Howard G, Meschia JF, Cushman M, Muntner P, Pullicino PM, McClure LA, Judd S, Howard VJ. Self-reported atrial fibrillation and risk of stroke in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. Stroke. 2011;42(10):2950–2953. doi: 10.1161/STROKEAHA.111.621367. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.NIAAA. Moderate and binge drinking. 2004 Available at http://www.niaaa.nih.gov/alcohol-health/overview-alcohol-consumption/moderate-binge-drinking.
- 26.Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reportedmeasure of medication adherence. Medical care. 1986;24:67–74. doi: 10.1097/00005650-198601000-00007. [DOI] [PubMed] [Google Scholar]
- 27.Conen D, Tedrow UB, Koplan BA, Glynn RJ, Buring JE, Albert CM. Influence of systolic and diastolic blood pressure on the risk of incident atrial fibrillation in women. Circulation. 2009;119:2146–2152. doi: 10.1161/CIRCULATIONAHA.108.830042. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.O'Neal WT, Soliman EZ, Qureshi W, Alonso A, Heckbert SR, Herrington D. Sustained pre-hypertensive blood pressure and incident atrial fibrillation: the Multi-Ethnic Study of Atherosclerosis. J Am Soc Hypertens. 2015;9(3):191–196. doi: 10.1016/j.jash.2015.01.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Vyssoulis G, Karpanou E, Adamopoulos D, Kyvelou SM, Tzamou V, Michaelidis A, Stefanadis C. Metabolic syndrome and atrial fibrillation in patients with essential hypertension. Nutr Metab Cardiovasc Dis. 2013;23(2):109–114. doi: 10.1016/j.numecd.2011.03.011. [DOI] [PubMed] [Google Scholar]
- 30.Pimenta E, Calhoun DA. Resistant hypertension: incidence, prevalence, and prognosis. Circulation. 2012;125(13):1594–1596. doi: 10.1161/CIRCULATIONAHA.112.097345. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Daugherty SL, Powers JD, Magid DJ, Tavel HM, Masoudi FA, Margolis KL, O'Connor PJ, Selby JV, Ho PM. Incidence and prognosis of resistant hypertension in hypertensive patients. Circulation. 2012;125(13):1635–1642. doi: 10.1161/CIRCULATIONAHA.111.068064. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Su G, Cao H, Xu S, Lu Y, Shuai X, Sun Y, Liao Y, Li J. Left atrial enlargement in the early stage of hypertensive heart disease: a common but ignored condition. J Clin Hypertens (Greenwich) 2014;16(3):192–197. doi: 10.1111/jch.12282. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Casaclang-Verzosa G, Gersh BJ, Tsang TM. Structural and Functional Remodeling of the Left Atrium: Clinical and Therapeutic Implications for Atrial Fibrillation. J Am Coll Cardiol. 2008;51(1):1–11. doi: 10.1016/j.jacc.2007.09.026. [DOI] [PubMed] [Google Scholar]
- 34.Tsang TS, Barnes ME, Abhayaratna WP, Cha SS, Gersh BJ, Langins AP, Green TD, Bailey KR, Miyasaka Y, Seward JB. Effects of quinapril on left atrial structural remodeling and arterial stiffness. Am J Cardiol. 2006;97(6):916–920. doi: 10.1016/j.amjcard.2005.09.143. [DOI] [PubMed] [Google Scholar]
- 35.Healey JS, Baranchuk A, Crystal E, Morillo CA, Garfinkle M, Yusuf S, Connolly SJ. Prevention of atrial fibrillation with angiotensin-converting enzyme inhibitors and angiotensin receptor blockers: a meta-analysis. J Am Coll Cardiol. 2005;45(11):1832–1839. doi: 10.1016/j.jacc.2004.11.070. [DOI] [PubMed] [Google Scholar]
- 36.Shroff SC, Ryu K, Martovitz NL, Hoit BD, Stambler BS. Selective aldosterone blockade suppresses atrial tachyarrhythmias in heart failure. J Cardiovasc Electrophysiol. 2006;17(5):534–541. doi: 10.1111/j.1540-8167.2006.00372.x. [DOI] [PubMed] [Google Scholar]
- 37.Go AS, Hylek EM, Phillips KA, Chang Y, Henault LE, Selby JV, Singer DE. Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the AnTicoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study. JAMA. 2001;285(18):2370–2375. doi: 10.1001/jama.285.18.2370. [DOI] [PubMed] [Google Scholar]
- 38.Wattigney WA, Mensah GA, Croft JB. Increased atrial fibrillation mortality: United States, 1980–1998. Am J Epidemiol. 2002;155(9):819–826. doi: 10.1093/aje/155.9.819. [DOI] [PubMed] [Google Scholar]
- 39.Haywood LJ, Ford CE, Crow RS, Davis BR, Massie BM, Einhorn PT, Williard A ALLHAT Collaborative Research Group. Atrial fibrillation at baseline and during follow-up in ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) J Am Coll Cardiol. 2009;54(22):2023–2031. doi: 10.1016/j.jacc.2009.08.020. [DOI] [PubMed] [Google Scholar]
- 40.Schoonderwoerd BA, Smit MD, Pen L, Van Gelder IC. New risk factors for atrial fibrillation: causes of 'not-so-lone atrial fibrillation'. Europace. 2008;10(6):668–673. doi: 10.1093/europace/eun124. [DOI] [PubMed] [Google Scholar]
- 41.Fox CS, Parise H, D'Agostino RB, et al. Parental atrial fibrillation as a risk factor for atrial fibrillation in offspring. Journal of the American Medical Association. 2004;291(23):2851–2855. doi: 10.1001/jama.291.23.2851. [DOI] [PubMed] [Google Scholar]
- 42.Gami AS, Hodge DO, Herges RM, et al. Obstructive sleep apnea, obesity, and the risk of incident atrial fibrillation. Journal of the American College of Cardiology. 2007;49(5):565–571. doi: 10.1016/j.jacc.2006.08.060. [DOI] [PubMed] [Google Scholar]
- 43.Abdulla J, Nielsen JR. Is the risk of atrial fibrillation higher in athletes than in the general population? A systematic review and meta-analysis. Europace. 2009;11(9):1156–1159. doi: 10.1093/europace/eup197. [DOI] [PubMed] [Google Scholar]
- 44.Sankaranarayanan R, Kirkwood G, Dibb K, Garratt CJ. Comparison of Atrial Fibrillation in the Young versus That in the Elderly: A Review. Cardiol Res Pract. 2013:976. doi: 10.1155/2013/976976. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.