BP Variability and Cardiovascular Autonomic Function in Relation to Forced Expiratory Volume

Original Research LUNG FUNCTION TESTING

BP Variability and Cardiovascular Autonomic Function in Relation to Forced Expiratory Volume A Population-Based Study Gunnar Engstro¨m, MD, PhD; Maria Gerhardsson de Verdier, MD, PhD; Magnus Dahlba¨ck, MD, PhD; Christer Janson, MD, PhD; and Lars Lind, MD, PhD

Background: Cardiovascular autonomic dysfunction is associated with increased incidence of cardiovascular diseases. This population-based study explored whether low FEV1 or low vital capacity (VC) is associated with autonomic dysfunction, as measured by spontaneous heart rate variability (HRV) and systolic BP variability (SBPV). Methods: SBPV and HRV were recorded during 5 min of controlled breathing in men and women who were 70 years of age. FEV1 and VC were recorded in 901 subjects. Of them, information on HRV and SBPV was available in 820 and 736 subjects, respectively. Measures of autonomic function, that is, SBPV in the low-frequency (LF) and high-frequency (HF) domains, HRV, and baroreceptor sensitivity (BRS), were studied in sex-specific quartiles of FEV1 and VC. Results: Low FEV1 was associated with high SBPV in the HF domain. The mean SBPV-HFs were 5.2, 4.5, 4.1, and 3.8 mm Hg, respectively, in subjects with FEV1 in the first (low), second, third, and fourth quartile (p < 0.001 [for trend]). This relationship persisted after adjustments for potential confounding factors. Low VC was significantly associated with high SBPV-HF in the crude analysis but not after adjustment for confounding factors. Neither FEV1 nor VC showed any significant relationship with BRS, HRV, or SBPV in the LF domain. Conclusion: In this population-based study, low FEV1 was associated with high SBPV in the HF domain. It is suggested that high beat-to-beat variability in BP could contribute to the increased (CHEST 2009; 136:177–183) cardiovascular risk in subjects with moderately reduced FEV1. Abbreviations: BMI ⫽ body mass index; BRS ⫽ baroreceptor sensitivity; CRP ⫽ C-reactive protein; CVD ⫽ cardiovascular disease; DBP ⫽ diastolic BP; HF ⫽ high frequency; HRV ⫽ heart rate variability; LF ⫽ low frequency; SBP ⫽ systolic BP; SBPV ⫽ systolic BP variability; SDNN ⫽ SD of the RR (NN) interval; VC ⫽ vital capacity

studies have shown that apparently healthy M any subjects with moderately reduced FEV or vital 1

capacity (VC) have increased risk of cardiovascular diseases (CVDs).1– 6 Reduced lung function has also been associated with increased proportion of fatal cardiac events and poor prognosis in patients undergoing coronary interventions.6 – 8 It has also been shown that the prevalence of ventricular arrhythmia is increased in subjects with low FEV1 or VC, which could contribute to the increased cardiovascular risk.3,9 The nature of this association is still controversial. However, it is well known that respiration and obstructive breathing could have several cardiovascular effects.10 –12 www.chestjournal.org

Respiration is a major drive force for the autonomic nervous system.11 Heart rate variability (HRV), BP variability, and baroreceptor sensitivity (BRS) are different measures of the cardiovascular autonomic function that are used for research purposes.13–15 Disturbed autonomic function has been associated with increased prevalence of different CVD risk factors,16,17 increased prevalence of ventricular arrhythmia,18 and with CVD.19 –22 Several studies23–26 have reported that patients with advanced COPD have altered the balance of the sympathetic and parasympathetic cardiovascular regulation. To our knowledge, there is no large populationbased study of cardiovascular autonomic function in CHEST / 136 / 1 / JULY, 2009

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relation to lung function in the normal range. The aim of the present study was to explore whether the cardiovascular autonomic function was related to FEV1 or VC in a population-based cohort of older men and women.

Materials and Methods Subjects The Prospective Investigation of the Vasculature in Uppsala Seniors27 is a population-based study of the cardiovascular health in the elderly. The main purpose of Prospective Investigation of the Vasculature in Uppsala Seniors was to explore the role of endothelium-derived vasodilation for the cardiovascular risk. Mailed invitations were sent to subjects who lived in Uppsala, Sweden, within 2 months after their 70th birthday. The subjects were randomly selected from the community register. A total of 1,016 men and women participated (participation rate, 50.1%). Spirometry was performed in 901 subjects. Subjects with frequent ectopic beats (ie, ⬎ 10%) were excluded (n ⫽ 36), as were those with atrial fibrillation (n ⫽ 25). Subjects were also excluded if they had a pacemaker or whenever data were inadequate owing to failure of arterial cannulation (11% of the sample) or technical disturbances. Thus, of the 901 subjects with data on lung function, data on HRV were available in 820 subjects. Of those 820 subjects, information about systolic BP variability (SBPV) was present in 736 subjects, and about BRS in 729 subjects. The Ethics Committee of the University of Uppsala approved the study, and the participants gave their informed consent. Assessment of Cardiovascular Risk Factors Prior to the examination, subjects completed a questionnaire concerning their medical history, regular medication use, and smoking habits. All subjects were investigated in the morning after an overnight fast, and no medication was taken on the day of the investigation. For the examination, participants were placed in the supine position in a quiet room, which was held at a constant temperature. Recordings of height, weight, and abdominal and hip dimensions were performed, and blood samples were taken and analyzed using standard laboratory techniques. BP was measured using a mercury sphygmomanometer. Hard physical activity was assessed using the following question: “How many times per week do you perform hard physical From AstraZeneca R&D (Drs. Engstro¨m, Gerhardsson de Verdier, and Dahlba¨ck), Lund, Sweden; the Department of Clinical Sciences (Dr. Engstro¨m), Malmo¨ University Hospital, Lund University, Lund, Sweden; and the Department of Medical Sciences (Drs. Janson and Lind), Uppsala University, Uppsala, Sweden. Drs. Engstro¨m, Gerhardsson de Verdier, and Dahlba¨ck are employed by AstraZeneca R&D. Dr. Lind has received research grants from AstraZeneca. Dr. Janson has no potential conflicts of interest. Manuscript received October 21, 2008; revision accepted January 23, 2009. Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestjournal. org/site/misc/reprints.xhtml). Correspondence to: Gunnar Engstro¨m, MD, PhD, AstraZeneca R&D, 205:3, 22187 Lund, Sweden; e-mail: Gunnar.Engstrom@ astrazeneca.com DOI: 10.1378/chest.08-2529

activity ⬎ 30 min (eg, running, swimming, tennis, football)?” The number of weekly occasions was used in the analysis. Information about physical activity was missing for 32 subjects (3.9%). This group was coded in a separate category (dummy variable) in order to keep these individuals in the multivariate analysis. Medications used for asthma or COPD, hypertension, and diabetes were assessed in the questionnaire. Diabetes was defined as a fasting whole-blood glucose concentration ⱖ 6.1 mmol/L or a history of diabetes according to the questionnaire results. Hypertension was defined as systolic BP (SBP) ⱖ 140 mm Hg, and/or diastolic BP (DBP) ⱖ 90 mm Hg, and/or drug treatment for hypertension. The question “Have you been told by a doctor that you have asthma, chronic bronchitis, COPD, or emphysema?” was used to assess the patient’s history of asthma or COPD. A similar question was used to assess the patient’s history of angina pectoris. Recordings of ECG, BP, and Breathing A six-precordial-lead ECG was recorded (Mingocard 7; Siemens Elema; Stockholm, Sweden). The BP was recorded via an intraarterial catheter in the brachial artery. Spontaneous breathing was allowed during the first 10 min. During the last 5 min, breathing was limited to a rate of 12 breaths/min (0.2 Hz). The ECG and BP signals were digitized at a sampling frequency of 500 Hz, and the breathing signal at 10 Hz. Artifacts were removed from the ECG, excluding nonadequate trigs (ectopic beats) and trigging unmarked R-peaks. BRS The sequence method was used to analyze BRS.28,29 A sequence was defined as a series of at least three consecutive heartbeats during which the SBP and the following beat-to-beat (RR) interval either increased or decreased by a minimum of 1 mm Hg per beat and 3 ms per beat, respectively. There was a one-beat delay between SBP and RR in the sequences. Custom-made software (based on Excel; Microsoft Inc; Redmond, WA) scanned the data and detected such sequences. Both increasing and decreasing slopes were analyzed. No minimal correlation coefficient was required for the consecutive RR and SBP changes. The number of valid slopes ranged between 4 and 99 for the subjects in the study. The mean value of the regression slopes was used as a measure of BRS. Spectral analysis of SBPV and RR-interval variations was performed with proprietary software (Ekman Biomedical Data AB; Gothenburg, Sweden [using MATLAB; Math-Works Inc; Natick, MA]). The 5-min segment of controlled breathing was used for analysis. The signal was linearly detrended, and a low-pass filter (fifth-order Butterworth) was subsequently applied using a cutoff frequency of 1 Hz. The power spectrum density of the signal was determined by using fast Fourier transform, which was carried out using the Welch algorithm. The data were divided into two blocks with a 50% overlap, and each block was windowed using the Hamming function. The powers of the RR interval and the SBPV were calculated in the high-frequency (HF) band (0.15 to 0.25 Hz) and the low-frequency (LF) band (0.03 to 0.15 Hz). The beat-to-beat variability in the time domain was measured as the SD of the RR (NN) interval (SDNN). Total variance of HRV was calculated as the square of the SDNN. Spirometry Spirometry was performed in accordance with American Thoracic Society recommendations30 (␣ spirometer; Vitalograph Ltd; Buckingham, UK). The best value from three recordings was used. The volumes were adjusted for height and were expressed as percent predicted values. The equations for the predicted values

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Table 1—Distribution of Risk Factors in Sex-Specific Quartiles of FEV1 Variables

Q1 (low)

Gender Men Women FEV1, % predicted Men Women Height, cm Men Women Smokers Angina Diabetes Any antihypertensive drug ␤-Blocker History of MI Asthma/COPD Medication for asthma or COPD Hard physical exercise, 30 min/wk SBP, mm Hg DBP, mm Hg Heart rate, 1/min BMI, kg/m2 WHR Men Women LDL, mmol/L HDL, mmol/L CRP,* mg/L

Q2

96 109

96 109

⬍85 ⬍91

Q3 96 109

Q4 (high)

p Value (for Trend)

96 109 ⬎108 ⬎115

85–97 91–104

97–108 104–115

175 ⫾ 7 162 ⫾ 5 19.1 10.9 13.2 33.7 25.4 8.4 17.8 11.3 0.53 ⫾ 1.2 152 ⫾ 23 79.1 ⫾ 11 62.5 ⫾ 9.1 27.5 ⫾ 4.8

175 ⫾ 6 162 ⫾ 6 8.3 10.8 16.1 40.4 30.2 8.3 7.1 4.4 0.52 ⫾ 1.0 154 ⫾ 22 78.7 ⫾ 10 62.5 ⫾ 9.7 27.1 ⫾ 4.5

176 ⫾ 7 162 ⫾ 6 7.8 4.4 8.8 24.9 15.6 4.4 3.5 2.4 0.75 ⫾ 1.3 148 ⫾ 24 77.5 ⫾ 10 61.4 ⫾ 7.9 27.0 ⫾ 4.2

176 ⫾ 6 162 ⫾ 6 3.9 4.9 7.8 25.5 11.7 3.9 4.4 3.9 0.72 ⫾ 1.3 147 ⫾ 21 78.8 ⫾ 9.5 62.4 ⫾ 8.9 26.7 ⫾ 3.4

0.97 ⫾ 0.06 0.87 ⫾ 0.07 3.35 ⫾ 0.87 1.58 ⫾ 0.50 1.65

0.95 ⫾ 0.06 0.87 ⫾ 0.07 3.36 ⫾ 0.92 1.50 ⫾ 0.40 1.30

0.93 ⫾ 0.06 0.86 ⫾ 0.06 3.45 ⫾ 0.85 1.54 ⫾ 0.44 1.16

0.93 ⫾ 0.06 0.86 ⫾ 0.04 3.44 ⫾ 0.84 1.49 ⫾ 0.35 1.12

⬍ 0.001 0.003 0.02 0.006 ⬍ 0.001 0.02 ⬍ 0.001 0.001 0.04 0.009 0.53 0.56 0.06 0.002

0.19 0.11 ⬍ 0.001

Values are given as the mean ⫾ SD or %, unless otherwise stated. HDL ⫽ high-density lipoprotein; LDL ⫽ low-density lipoprotein; MI ⫽ myocardial infarction; WHR ⫽ waist/hip ratio; Q ⫽ quartile. *Values are given as the geometric mean.

were computed using linear regressions of 186 male and 252 female never-smokers from the present cohort. The equations for men were as follows: FEV1 (in liters) ⫽ height (in centimeters) ⫻ 0.035 ⫺ 3.12

subjects with this medication. CRP and all measures of autonomic function were log normalized due to the skewed distributions. To facilitate the interpretation of the log-transformed values, the antilog values (ie, geometric means) were calculated and presented in the tables.

VC (in liters) ⫽ height (in centimeters) ⫻ 0.052 ⫺ 5.10 The equations for women were as follows: FEV1 (in liters) ⫽ height (in centimeters) ⫻ 0.025 ⫺ 2.066 VC (in liters) ⫽ height (in centimeters) ⫻ 0.040 ⫺ 3.82 Statistical Analysis Logistic regression (for dichotomous variables) and one-way analysis of variance (for continuous variables) were used to compare risk factors between quartiles of FEV1 and VC. The linear trends over the quartiles of FEV1 and VC were used in all analyses. The analysis of variance model was extended to a general linear model in order to adjust the relationships between lung function and measures of autonomic function for potential confounding factors. Significance testing of the relationships between lung function and risk factors was used to identify confounding factors. The multivariate analyses were adjusted for angina pectoris, diabetes, smoking, use of ␤-blocker, C-reactive protein (CRP), body mass index (BMI), waist/hip ratio, history of myocardial infarction, physical activity, and SBP. Because of the potential confounding effects of ␤-blocker medication, all multivariate analyses were repeated after exclusion of www.chestjournal.org

Results Distribution of Risk Factors in Relation to FEV1 A total of 820 subjects (384 men, 436 women) had complete data on SDNN and spectral analysis of HRV. Data on SBPV were available for 736 subjects (350 men, 386 women), and data on BRS were available for 729 subjects. Table 1 presents the distribution of risk factors in sex-specific quartiles of FEV1. As expected, many of the cardiovascular risk factors showed inverse significant relationships with FEV1. There was no significant relationship between FEV1 and blood lipids or heart rate. Cardiovascular Autonomic Function in Relation to FEV1 Table 2 presents the relationships between different measures of HRV in relation to sex-specific quartiles of CHEST / 136 / 1 / JULY, 2009

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Table 2—Heart Rate Variability in Sex-Specific Quartiles of FEV1 Variables

Q1 (low)

Q2

Q3

Q4 (high)

Gender, No. Men Women SDNN, ms Geometric mean Adjusted mean* HRV, total variance (ms2) Geometric mean Adjusted mean* HRV-HF (ms2) Geometric mean Adjusted mean* HRV-LF, ms2 Geometric mean Adjusted mean* HRV-LF/HF ratio Geometric mean Adjusted mean*

96 109 29.7 (8.3–138) 30.5 30.9 881 (69–19,191) 932 956 131 (3–3,047) 131 135 150 (2–9,875) 162 163 1.22 (0.12–14) 1.24 1.21

96 109 30.3 (6.1–110) 30.7 31.1 920 (37–12,038) 940 967 107 (7–1,925) 112 115 157 (6–9,019) 162 167 1.44 (0.09–9.4) 1.44 1.46

96 109 31.7 (11–153) 31.0 30.5 1005 (115–23,532) 962 932 129 (4–5,740) 131 126 176 (17–15,120) 170 164 1.25 (0.09–9.5) 1.30 1.31

96 109 31.0 (9–122) 30.6 30.1 963 (80–14,894) 936 903 116 (8–1,768) 115 109 124 (13–2,282) 149 144 1.25 (0.22–10.5) 1.30 1.32

p Value (for Trend)

0.90 0.52 0.90 0.52 0.51 0.18 0.56 0.28 0.87 0.64

Values are given as median (range), unless otherwise indicated. See Table 1 for abbreviation not used in the text. *Presented as geometric means, adjusted for angina, diabetes, smoking, use of ␤-blocker, log CRP, BMI, waist/hip ratio, history of myocardial infarction, physical activity, SBP.

FEV1. FEV1 showed no significant relationship with SDNN, total variance of HRV, HRV-LF, HRV-HF, or LF/HF ratio. The results were essentially unchanged after adjustment for confounding factors. SBPV-HF showed a significant relationship with FEV1, with higher BP variability in subjects with low FEV1 (Table 3). This relationship persisted after adjustments for potential confounding factors (p ⫽ 0.005). The results also remained statistically significant after the exclusion of subjects with a medical history of drug treatment for asthma or COPD (not shown). Figure 1 presents geometric mean values (95% confidence intervals) for the relationship between quartile of FEV1 and SBPV-HF in categories of sex,

smoking, and hypertension. The relationships were largely consistent in these groups, and the p values for the trends reached statistical significance (p ⬍ 0.05) in all subgroups except in the smokers. The results were essentially unchanged when subjects using ␤-blocker medication were excluded. SBPV-HF was still significantly associated with quartiles of FEV1. No significant relationships were observed for other measures of autonomic function. Cardiovascular Autonomic Function in Relation to VC SBPV-HF was significantly associated with the quartiles of VC before adjustments. The geometric

Table 3—SBP Variability and Baroreceptor Sensitivity in Sex-Specific Quartiles of FEV1 Variables

Q1 (low)

Q2

Q3

Q4 (high)

Gender, No. Men Women SBPV-HF, mm Hg Geometric mean Adjusted mean* SBPV-LF, mm Hg Geometric mean Adjusted mean* BRS slope, ms/mm Hg Geometric mean Adjusted mean* Slopes used in calculation of BRS

87 97 5.65 (0–61) 5.15 4.85 4.0 (0.45–45) 3.94 4.06 5.47 (1.6–28.2) 5.34 5.53 38 (4–99)

88 96 4.77 (0.6–31) 4.55 4.56 4.9 (0.50–80) 4.76 4.78 5.20 (1.7–29.7) 5.33 5.39 34 (4–97)

88 96 4.10 (0–27.6) 4.12 4.27 4.0 (0.30–38) 3.97 3.99 5.65 (1.8–18.4) 5.68 5.48 35 (6–88)

87 97 4.00 (0.7–21) 3.81 3.88 4.1 (0.40–41) 4.32 4.21 5.52 (2.0–21.9) 5.49 5.39 35 (5–87)

p Value (for Trend)

⬍ 0.001 0.005 0.72 0.82 0.38 0.71 0.58

Values are presented as the median (range), unless otherwise indicated. See Table 1 for abbreviation not used in the text. *Presented as geometric means, adjusted for angina, diabetes, smoking, use of ␤-blockers, log CRP, BMI, waist/hip ratio, history of myocardial infarction, physical activity, and mean arterial SBP. 180

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Men

Q4

Q2

Q3

Q1

Women Non-smokers Smokers Normal BP Hypertension 2

3

4

5

6

7

8

9

SBPV-HF (mmHg) Figure 1. SBPV-HF by quartile of FEV1 in categories of sex, smoking, and hypertension. From the top to the bottom in each of the categories, the error bars indicate geometric mean and 95% confidence intervals for subjects with FEV1 in quartile (Q) 1 (low) to Q4 (high). The p value was ⬍ 0.05 in all subgroups except in smokers.

mean values, from the lowest to the highest quartiles of VC, were 4.72, 4.57, 4.31, and 3.95 mm Hg, respectively (p ⫽ 0.022 [for trend]). However, this relationship was clearly nonsignificant after adjustment for potential confounding factors in the general linear model (not shown). The relationships between the quartiles of VC and SDNN, total variance of HRV, HRV-LF, HRV-HF, HRV-LF/HF ratio, BRS, and SBPV-LF, respectively, were all nonsignificant, both in the unadjusted and the adjusted analysis (not shown). Discussion The purpose of this population-based study was to explore whether low FEV1 or VC is associated with autonomic dysfunction, as measured by HRV and SBPV. SBPV in the HF domain was significantly higher in subjects with low FEV1. This finding was consistent in different categories of smoking and hypertension, and the relationship persisted after adjustments for several risk factors. There was no relationship between FEV1 and different measures of HRV. Previous studies22,31,32 have reported increased incidence of cardiovascular events and increased organ damage in subjects with high BP variability, independently of the mean BP. In a large populationbased study, Mancia et al22 reported that “erratic” www.chestjournal.org

beat-to-beat variations in DBP substantially increased the cardiovascular risk, even though the magnitude of the BP variations was modest. Beat-tobeat variations in DBP were associated with poor outcome in a cohort of patients with ischemic stroke.33 High BP variability has also been associated with elevated levels of different cardiovascular risk factors.16,17,21 Hence, even though no follow-up was available in this study, there are reasons to believe that high SBPV is associated with increased incidence of CVD. HRV and BRS are well-established measures of autonomic function.14,34 These measures showed no significant relationships with FEV1 or VC in this study, however. This suggests that autonomic dysfunction, as assessed by reduced HRV, is less important for the relationship between moderately reduced FEV1 and CVD. Studies of patients23–26 with advanced COPD have reported impaired autonomic function compared to control subjects. The present study of HRV in elderly subjects is not in accordance with these studies, and we can only speculate about the reasons for this difference. It is possible that reduced HRV only is associated with quite severe pulmonary dysfunction and not with reduced FEV1 within the normal range. Hypoxia has been associated with long-lasting sympathetic activation in healthy subjects.35 Even though some studies23 have reported increased sympathetic activation even in normoxic COPD patients, it is still possible that intermittent or nocturnal hypoxia could cause autonomic dysfunction in COPD patients. In line with this hypothesis, noninvasive nocturnal mechanical ventilation has been associated with improved HRV in COPD patients.24 Dyspnea and respiratory discomfort is often perceived in COPD patients, and it is conceivable that this could also affect the autonomic function. However, our results are consistent with a study36 of stable patients with COPD, which reported correlations between HRV and oxygenation status, but not between HRV and FEV1/VC. In contrast to HRV and BRS, it is controversial to what extent SBPV-HF reflects autonomic cardiovascular function.34 Human experimental studies34,37 have shown that SBPV-HF is strongly influenced by mechanical effects of breathing and intrathoracic pressure, whereas the role of autonomic function is less clear. Even though breathing was controlled in the present study, it is possible that the breathing patterns or the reduced lung function per se could increase the SBPV-HF. Many studies have reported increased incidence of CVD in apparently healthy subjects with moderately reduced FEV1. These relationships have generally remained significant after adjustments for potential confounding factors, and significant relationships CHEST / 136 / 1 / JULY, 2009

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have been reported from studies of never-smokers.5 Low FEV1 or VC has been associated with many different cardiovascular risk factors, including inflammation,2,4 smoking, arrhythmia,3,9 and so on. Longitudinal studies38 – 41 have reported that low FEV1 or FVC is associated with an increased risk of the development of hypertension and diabetes. Hence, the relationships between lung function and the incidence of CVD are complex, and there is little doubt that several factors are involved. Based on the present results, it is reasonable to suggest that increased SBPV-HF is another factor that contributes to this relationship. The participation rate was 50%, which is a limitation of the study. Based on a health questionnaire sent to 100 consecutive nonparticipants, the major difference between participants and nonparticipants was a higher incidence of stroke in those unwilling to participate.27 The study sample was an elderly white cohort from the general population. The subjects were approximately 70 years of age, and individuals with high cardiovascular risk often die before that age. Selective mortality would reduce the relationships between lung function and autonomic function, if anything. Hence, there is little reason to believe that selective mortality or a low participation rate explains the relationship between SBPV-HF and low FEV1. We cannot rule out, however, that selection effects could explain the absence of significant relationships between FEV1 and other measures of autonomic function. The registration of cardiovascular autonomic function was performed in a standardized manner during 5 min of controlled breathing. However, it has been shown42 that breathing control per se could affect the autonomic balance, and we do not know whether the relationships between FEV1 and autonomic function would be the same during spontaneous breathing. There was no relationship between FEV1 and HRV in this population-based study. However, SBPV in the HF domain was significantly higher in subjects with low FEV1. It has been suggested that this relationship could contribute to the increased cardiovascular risk in subjects with moderately reduced FEV1. References 1 Young RP, Hopkins R, Eaton TE. Forced expiratory volume in one second: not just a lung function test but a marker of premature death from all causes. Eur Respir J 2007; 30:616 – 622 2 Sin DD, Wu L, Man SF. The relationship between reduced lung function and cardiovascular mortality: a populationbased study and a systematic review of the literature. Chest 2005; 127:1952–1959

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