THE JOURNAL OF ALTERNATIVE AND COMPLEMENTARY MEDICINE Volume 20, Number 8, 2014, pp. 642–648 ª Mary Ann Liebert, Inc. DOI: 10.1089/acm.2013.0280
Acute Effect of Breathing Exercises on Heart Rate Variability in Type 2 Diabetes: A Pilot Study Carmine R. Grieco, PhD,1 Sheri R. Colberg, PhD,2 C. Thomas Somma, PhD,3 Andrew G. Thompson, MS,4 and Aaron I. Vinik, MD, PhD 5
Abstract
Background: Type 2 diabetes (T2D) is associated with autonomic nervous system damage resulting in reduced heart rate variability (HRV). Limited evidence suggests yogic breathing exercises may improve indices of HRV. Purpose: The purpose of this study was to evaluate the effect of two commonly used yogic breathing exercises on HRV in T2D versus an age-matched, normoglycemic (CON) population. Methods: Twelve (12) subjects with T2D (7 female, 5 male; 54.9 – 7.4 years) and 14 CON subjects (12 female, 2 male; 54.7 – 6.8 years) participated in a breathing protocol consisting of two 10-min bouts of randomly assigned uni-nostril breathing (UNB). UNB bouts were preceded and followed by 5-min periods of dual-nostril paced breathing (PB). HRV was measured by standard deviation of normal-to-normal consecutive heartbeats (SDNN), square root of the mean squared differences in successive normal heartbeats (RMSSD), and total spectral power (TP). All data (except instantaneous heart rate) were log transformed to improve normality. Within-group comparisons were analyzed using analysis of variance with repeated measures, whereas betweengroup comparisons were analyzed using independent-samples t-test. Results: Between-groups comparisons revealed significant reductions in all measures of HRV at nearly all time points in T2D compared to CON. Within-group comparison demonstrated no significant effect of UNB or PB on HRV in CON. In the T2D group, however, left UNB significantly reduced mean HR ( - 1.2 bpm, p < 0.05) as well as TP ( p < 0.05). Conclusions: In summary, neither UNB nor PB had an impact upon HRV in a healthy older population and had a minimal impact in T2D.
Introduction
T
he prevalence of type 2 diabetes mellitus (T2D) has reached epidemic proportions in the United States and now represents > 1 out of every 10 adults.1 An additional 29.5% of the adult population has prediabetes, a state characterized by impaired fasting glucose and/or impaired glucose tolerance.1 Furthermore, it is predicted that the number of people with diabetes will nearly double within the next 3 decades.2 Damage to the autonomic nervous system (ANS) is a common complication of T2D and may in fact occur prior to diagnosis.3 ANS damage frequently manifests as autonomic
neuropathy (AN), a serious neurological condition that may have a deleterious effect on any organ of the body.4 A characteristic sign of AN is a reduction in heart rate variability (HRV), measured as the time oscillation between successive heartbeats and representing the input of autonomic control over the cardiac cycle in response to changing physiologic demands. HRV is a measure of the underlying tone or balance between sympathetic and vagal (parasympathetic) inputs, with high variability representing an enhanced adaptive ability and low variability reflecting a diminished capacity. A healthy cardiovascular control system will have a high level of complexity, while an aged or diseased system will show a loss of complexity or variability. In fact, in a study of
1
Department of Education, Glenville State College, Glenville, WV. Human Movement Sciences Department and 3Department of Medical Laboratory and Radiation Sciences, Old Dominion University, Norfolk, VA. 4 Department of Kinesiology, Auburn University, Auburn, AL. 5 Strelitz Diabetes Institute, Eastern Virginia Medical School, Norfolk, VA. 2
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1987 older individuals (55–74 years), Ziegler et al.5 determined that the primary factor predicting decreased HRV was the presence of diabetes. Reduced HRV has also been shown to be an early predictor of macrovascular disease, increasing carotid artery atherosclerosis,6 and all-cause mortality in T2D.7 Higher levels of HRV are associated with increased cardiorespiratory fitness,8 and exercise training has demonstrated an important ability to improve HRV in T2D.9,10 Importantly, though, individuals with T2D are less likely to participate in exercise and adhere to an exercise regimen.11,12 Additionally, a frequent complication of T2D is exercise intolerance and a low functional capacity,13 which contributes to the low exercise participation and adherence rates among individuals with T2D. Therefore, any exercise interventions that have a higher adherence rate than standard exercise programming may play a clinically important role in the treatment of T2D. Yoga is an ancient form of physical and psychologic training that has experienced a surge in popularity in the United States.14 The modern practice of yoga as an exercise therapy typically emphasizes the two disciplines of hatha yoga (physical postures) and pranayama (breathing exercises). Prior studies have demonstrated that hatha and hatha/ pranayama yoga training are viable adjunctive therapies for T2D. Importantly, yoga training is also associated with a higher adherence rate than traditional exercise training.15 Many studies support the concept that yogic breathing exercises, independent of hatha yoga practice, may have an ability to influence cardiovascular control via the ANS. Pranayama is associated with improved autonomic tone, specifically increased parasympathetic (vagal) activity.16 Several studies have also demonstrated significant improvements in cardiovascular variables with pranayama that may be attributable to alterations in autonomic tone.17–19 Nevertheless, only limited data investigating the effect of pranayama on HRV exist. Furthermore, to our knowledge this is the first study specifically investigating the effect of pranayama on HRV in T2D. Pranayama represents a simple, inexpensive, and noninvasive tool that may play a role in improving HRV and, more specifically, parasympathetic tone. Therefore, the purpose of this study was to determine the extent to which two commonly employed yogic breathing techniques (slow, paced breathing [PB] and uni-nostril breathing [UNB]) affect HRV in individuals with T2D. Methods Subjects
Twelve (12) subjects with uncomplicated T2D and 14 normoglycemic subjects participated in this investigation. All individuals with T2D were treated with oral antihyperglycemic drugs and/or lifestyle management (diet and exercise). All subjects were prescreened via a health screening questionnaire to determine eligibility. Exclusionary criteria included congested nasal passages (i.e., common cold or allergies), a deviated septum, congestive heart failure, myocardial infarction, arrhythmia or any cardiovascular event in the previous year, or liver, kidney, or pulmonary disease. The study was approved by the Institutional Review Board and all subjects provided signed informed consent.
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Protocol
Subjects were asked to refrain from eating within 3 hours of testing or consuming any caffeine-containing products prior to testing on the assigned day. Each subject was securely fitted with a Bioharness (Zephyr Technology Corp., Annapolis, MD), worn on the chest similar to a heart rate monitor. After premoistening the electrodes on the Bioharness, which is similar to a standard heart rate monitor and consists of a single Velcro-adjusted strap, it was placed against the skin, under clothing, at the level of the sternum. Participants were positioned in a comfortable chair with their feet flat on the ground and instructed to relax and to speak and move as little as possible prior to receiving detailed verbal instructions regarding the breathing protocol. A laptop computer displaying a breath-pacing program was positioned at eye level to provide both auditory and visual cues for breath pacing (E-Z Air Plus, Thought Technology Ltd., West Chazy, NY). For the UNB portion of the protocol, the subjects were instructed to use the contralateral hand to depress and seal off the assigned nostril by placing a single finger (the ring finger) over the nasal vestibule and depressing the tip of the finger until the cessation of air flow was confirmed. Briefly, the breathing protocol consisted sequentially of 5 minutes of spontaneous breathing (nonpaced) (Baseline 1); 2 minutes of spontaneous breathing while standing in place (Stand 1); 5 minutes of paced breathing at a rate of 6 breaths per minutes (Baseline 2); 10 minutes of randomly assigned UNB (UNB1); 5 minutes of paced breathing (Baseline 3); 10 minutes of UNB (opposite nostril) (UNB2); and 2 minutes of paced breathing while standing in place. The slow, paced breathing portion of the protocol was adjusted so each inhale was 4 seconds and each exhale was 6 seconds in duration. The entire breathing protocol lasted 39 minutes. Heart rate variability
HRV data were recorded on a Bioharness collecting at a sampling rate of 250 Hz. The data were then exported as a text file to the HRV analysis software program Kubios HRV 2.0 (Biosignal Analysis and Medical Imaging Group, Department of Physics, University of Kuopio, Finland). Data were visually inspected on a computer monitor to minimize presence of artifact. Detrending of raw data was performed according to Tarvainen et al.,20 and power frequency analysis was performed using a fast Fourier transform with Welch’s periodogram (256s window with 50% overlap). Time domain HRV measurements included mean RR interval, standard deviation of the normal-to-normal consecutive heartbeats (SDNN), and square root of the mean squared differences of successive normal heartbeats (RMSSD). The SDNN is a global measure of variability, while the RMSSD reflects only the vagal influence.21 Frequency domain measurements included total power (TP), presented as absolute power (ms2). TP is considered a marker of total variance.21 Statistics
Data analyses were performed with PASW 17.0 (SPSS, Chicago, IL). As the HRV data were not normally distributed, all of them were logarithmically transformed prior to analysis to improve normality (with the exception of
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Table 1. Log-Transformed Time and Frequency Domain Measurements of Heart Rate Variability (Mean – Standard Error of Mean) Mean HR
Baseline First Stand Baseline 2 LNB Baseline 3 RNB Last Stand Overall
SDNN
Total power (ms2)
RMSSD
CON
T2D
CON
T2D
CON
T2D
CON
T2D
69.7 – 3.43 75.3 – 2.5 67.0 – 2.4 67.4 – 2.2 67.5 – 1.8 67.7 – 2.0 71.4 – 1.9 68.5 – 2.4
73.7 – 4.01 80.1 – 4.1 72.0 – 3.5 70.1 – 2.8{ 70.1 – 2.9 70.9 – 3.1 79.1 – 3.4* 71.3 – 2.9
1.91 – 0.10 2.00 – 0.13 2.06 – 0.08 1.96 – 0.08 2.00 – 0.08 1.94 – 0.08 2.08 – 0.10 2.03 – 0.07
1.64 – 0.33 1.80 – 0.10 1.72 – 0.10* 1.60 – 0.20* 1.63 – 0.07* 1.63 – 0.08* 1.73 – 0.10* 1.76 – 0.06*
1.92 – 0.12 1.87 – 0.15 2.01 – 0.11 1.89 – 0.11 1.93 – 0.10 1.88 – 0.10 2.04 – 0.11 1.97 – 0.09
1.53 – 0.42* 1.58 – 0.15 1.62 – 0.12* 1.42 – 0.07* 1.47 – 0.08* 1.45 – 0.09* 1.53 – 0.14* 1.58 – 0.08*
3.67 – 0.26 3.66 – 0.32 3.92 – 0.18 3.86 – 0.17 3.95 – 0.18 3.87 – 0.21 3.95 – 0.23 3.99 – 0.19
3.07 – 0.21 3.08 – 0.24 3.30 – 0.22 3.07 – 0.12{ 3.21 – 0.13 3.17 – 0.17* 3.22 – 0.20* 3.41 – 0.13*
*Significant difference vs. CON ( p < 0.05). { Significant difference vs. Overall Mean HR within T2D ( p < 0.05). { Significant difference vs. Last Stand ( p < 0.05). SDNN, standard deviation of the normal-to-normal consecutive heartbeats; RMSSD, square root of the mean squared differences of successive normal heartbeats; CON, control group; T2D, type 2 diabetes; RNB, right-nostril breathing; LNB, left nostril breathing; HR, heart rate.
Baseline RMSSD in the T2D group was significantly lower than CON ( p = 0.03). Baseline 2 SDNN and RMSSD
were significantly lower in T2D compared to CON ( p = 0.01 and p = 0.02, respectively) (Table 1). Left-nostril breathing (LNB) SDNN, RMSSD, and TP were significantly lower in T2D compared to CON ( p = 0.001, p = 0.002, and p = 0.001, respectively) (Fig. 1). Baseline 2 SDNN and RMSSD were significantly lower in T2D than CON ( p = 0.003 and p = 0.002, respectively). Right-nostril breathing (RNB) SDNN, RMSSD, and TP were significantly lower in T2D compared to CON ( p = 0.01, p = 0.004, and p = 0.01, respectively). Baseline 3 measurements of SDNN and RMSSD were significantly lower in the T2D group ( p < 0.05) (Fig. 2). Last Stand SDNN, RMSSD, and TP were significantly lower in T2D than in CON ( p = 0.02, p = 0.007, and p = 0.02, respectively). Mean HR during Last Stand was significantly higher in the T2D group (7.7 bpm, p < 0.05) (Fig. 3). Overall SDNN, RMSSD, and TP were significantly lower in T2D than in CON ( p = 0.009, p = 0.005, and p = 0.02, respectively). See Figures 4, 5, and 6 for full protocol comparison of SDNN, RMSSD, and TP.
FIG. 1. Log-transformed standard deviation of the normalto-normal consecutive heartbeats (SDNN) and square root of the mean squared differences of successive normal heartbeats (RMSSD) values during left-nostril breathing in type 2 diabetes (T2D) versus control (CON) subjects. *Significantly less than CON group ( p < 0.05).
FIG. 2. Mean heart rate during Stand 2 comparing subjects with T2D to CON subjects. *Significantly higher than CON group ( p < 0.05).
instantaneous heart rate data). Within-group comparisons were analyzed using analysis of variance with repeated measures on eight time points (Baseline 1, Stand 1, Baseline 2, UNB 1, Baseline 3, UNB 2, Stand 2, and Overall). Betweengroup comparisons were analyzed using independent samples t-tests. Results Subjects
There was no significant difference in age between the T2D group (7 female, 5 male; 54.9 – 7.4 years) and control group (CON) (12 female, 2 male; 54.7 – 6.8 years). The average length of diagnosed diabetes within the T2D group was 8.4 – 6.2 years. Between groups
BREATHING AND SYMPATHOVAGAL BALANCE IN DIABETES
FIG. 3. Log-transformed SDNN and RMSSD during Baseline 3 comparing the T2D versus CON groups. *Significantly less than CON group ( p < 0.05). Within groups
In the T2D group, the LNB protocol resulted in a significantly lower mean heart rate (-1.2 bpm, p = 0.014) in comparison to the overall protocol measures (Fig. 7). The LNB also resulted in a significant decrease in TP compared to Last Stand (-0.15, p < 0.05). There were no other significant interactions within the CON or T2D groups. Discussion
The purpose of this investigation was to examine the acute effect of two common styles of yogic breathing exercises on autonomic tone in individuals with T2D and age-matched controls. Our findings indicated two primary results: (1) neither UNB nor PB had any effect on HRV within an older (54.7 – 6.8 years) normoglycemic group, and (2) the effect within the T2D group was minimal, resulting in a small, but significant, decrease in HR during LNB in comparison to overall HR and a significant decrease in TP during LNB in comparison to the Last Stand. A betweengroups comparison demonstrated significant reductions in
FIG. 4. Comparison of SDNN between CON and T2D groups across 39-minute breathing protocol. *Significantly less than CON group ( p < 0.05). LNB, left-nostril breathing; RNB, right-nostril breathing.
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FIG. 5. Comparison of RMSSD between CON and T2D groups across 39-minute breathing protocol. *Significantly less than CON group ( p < 0.05).
nearly all measures of HRV in the T2D individuals compared to the CON group, which supports previous research showing reduced HRV in T2D. The results of the present study, which investigated the acute effect of pranayama, are in opposition to several previous training studies that have demonstrated a long-term effect of pranayama upon indices of cardiovascular and autonomic-related control in predominantly young and healthy populations. For example, an early study by Telles et al.22 found that 4 weeks of daily LNB significantly increased galvanic skin resistance, indicating a reduction in sympathetic outflow to the sweat glands in healthy, young males. Similarly, Pal et al.19 found that 1 hour of daily slowbreathing pranayama significantly decreased resting HR and HR response to standing in healthy, young males. Likewise, Udupa et al.23 demonstrated that 3 months of pranayama training (20 minutes per day, 5 days per week) significantly lowered resting HR among adolescent boys in comparison to a control group. More recently, Turankar et al.24 showed
FIG. 6. Comparison of total power between CON and T2D groups across 39-minute breathing protocol. *Significantly less than CON group ( p < 0.05). {Significantly different from Last Stand ( p < 0.05).
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FIG. 7. Mean heart rate (HR) in T2D subjects during the LNB compared to the overall mean HR through the entire breathing protocol. *Significantly less than overall mean HR ( p < 0.05).
that as little as 7 days of pranayama training may reduce a marker of sympathetic nervous system excitation (galvanic skin response). Most prior investigations, however, differ from the present one in several important ways, which may help to explain the difference in outcomes: (1) they included training interventions that lasted from 7 days up to 3 months; (2) study populations were typically young, healthy, and male; (3) in several studies, pranayama training is used concurrently with other modalities (i.e., the physical training of hatha yoga and/or the mental training or meditation, which is commonly called dharana or dhyana); (4) frequently the study population has a prior history of pranayama training; and (5) importantly, few studies measured HRV directly, but rather used a surrogate measure of autonomic function (e.g., resting heart rate or blood pressure). Nevertheless, studies involving the chronic effect of pranayama training have provided consistently positive results. While the evidence supporting a training effect of pranayama on autonomic function or surrogate measures of autonomic function is substantial, fewer studies have demonstrated an acute effect. Additionally, such results have been equivocal and inconsistent. For example, an investigation of the acute effect of a single bout of 15 minutes of alternate-nostril breathing (breathing through right and left nostril alternately) in young (25.6 years), healthy male subjects found no significant effect upon HRV.25 In contrast, Shannahoff-Khalsa and Kennedy26 found that a single bout of alternate-nostril breathing conducted for 15 minutes significantly altered HR, with left-nostril breathing decreasing and right-nostril breathing increasing resting HR in older (45.1 years) experienced pranayama practitioners. In one of the few published studies measuring parameters of HRV, Raghuraj and Telles27 recruited 21 young, healthy male volunteers with previous pranayama training. Subjects participated in a protocol that involved 7.5-minute epochs of right-nostril, left-nostril, and alternate-nostril breathing. Right and left nostril breathing had no significant effect upon HRV. Alternate-nostril breathing, however, significantly increased low-frequency power (a metric of sympathetic drive) while simultaneously decreasing high-frequency power (a metric of vagal drive). Similar to the present investigation, our 10-minute epochs of RNB and LNB demonstrated no
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effect upon HRV in older, but normoglycemic, subjects. Contrarily, the T2D group showed a reduction in total power during LNB. Given that sympathetic activation typically results in a reduction of total power, this provides some evidence of sympatho-excitation with LNB in a T2D population. Perhaps the best evidence linking the acute effect of yogic breathing exercises to surrogate measures of autonomic function was a study by Pramanik et al.28 Using a pharmaceutical blockade of parasympathetic stimulation, researchers compared the effect of 5 minutes of slow pranayama on resting heart rate and blood pressure among 39 young participants (an additional 10 subjects received the parasympathetic nervous system (PNS) blockade 30 minutes prior to pranayama). Results indicated significant reductions in diastolic and systolic blood pressure in the group without PNS blockade, and no change within the PNS blockade group. This mediation of resting blood pressure is suggestive of an increase in vagal outflow. There was, however, no direct measurement of HRV. The inconsistency within acute studies is likely a result of different methodological approaches, which influence the potential mechanism through which pranayama exerts it autonomic-modifying effect. While there is no clear consensus on how pranayama works, it has been hypothesized that the autonomic nervous system is functionally reset through stimulation of slowly adapting pulmonary stretch receptors (SAR) and hyperpolarization of fibroblasts located within connective tissue found within the lungs.17 Located within smooth muscle of the airways, the SARs, a class of pulmonary vagal receptor,29 continuously gauge tension within the elastic components of the tracheobronchial tree. The structure and function of SARs remains controversial, however. SARs have been found to play a role in systemic vascular tone and heart rate,17 potentially explaining the greater effect noted in training studies as opposed to acute studies. The consistent modification of cardiovascular and autonomic-related variables demonstrated in training studies and the equivocal findings of acute studies suggests a potential ‘‘threshold’’ effect of vagal afferents (i.e., SARs). If the threshold is met, through successive periods of training, vagal outflow is enhanced; anything below the threshold, however, does not alter vagal afferent activity. Further clarification of the interplay between the autonomic nervous system and afferent lung receptors will be needed before the potential mechanism of action underlying pranayama may be elucidated. To our knowledge, this is the first study that has investigated the effect (either acute or chronic) of yogic breathing exercises on HRV in a T2D population. We originally hypothesized that an acute bout of paced and UNB pranayama would manifest as changes in HRV in both normoglycemic and T2D groups, with greater alterations observed in the T2D population. The results of the investigation, however, provide only minimal support for our hypothesis. These results are largely in accord with the equivocal findings of other acute studies, but run at odds with the preponderance of training studies. The present investigation does have several limitations and must be viewed in the context of the results of previous research. The divergence of our findings from previous studies may be explained by several factors. Most importantly, it is possible that the small subject population,
BREATHING AND SYMPATHOVAGAL BALANCE IN DIABETES
combined with the relatively large variance of the unadjusted data, resulted in a type II error. Secondly, previous studies have used subject populations that are predominantly young, healthy, male and frequently, have prior pranayama training. In contrast, our subjects were older and predominantly female (73%), with an unequal distribution of female subjects between the two groups. Thirdly, this is the first study, to our knowledge, that has investigated the effect of an acute bout of pranayama in individuals with T2D. Without a more clear understanding of the underlying mechanism of action, it is difficult to predict the effect of differing subject populations on study outcomes. While the potential therapeutic effect of pranayama on autonomic function, especially for individuals with T2D, remains an intriguing prospect, more targeted research is necessary to explore the mechanism(s) of action underlying the autonomic-modifying effect of pranayama. Conclusions
In summary, our data indicate a clinically small, but significant, effect of UNB on resting HR and HRV in a population of older individuals with T2D. Slow, paced breathing and UNB, however, had no impact upon resting HR or HRV in an older, normoglycemic population. Nevertheless, there is a growing body of evidence linking yogic-style breathing exercises with autonomic modulation and cardiovascular control. Given the established association between vagal modulation and cardiovascular complications, and the current popularity of yoga and the relative ease of yogic breathing techniques, further research into the autonomic-modifying effects of pranayama is warranted as this shows some promise as an adjunctive therapy in the treatment of type 2 diabetes. Author Disclosure Statement
No competing financial interests exist. References
1. Cowie CC, Rust KF, Ford ES, et al. Full accounting of diabetes and pre-diabetes in the U.S. population in 1988– 1994 and 2005–2006. Diabetes Care 2009;32:287–294. 2. Chaturvedi N. The burden of diabetes and its complications: Trends and implications for intervention. Diabetes Res Clin Pract 2007;76(Suppl 1):S3–S12. 3. Singh JP, Larson MG, O’Donnell CJ, et al. Association of hyperglycemia with reduced heart rate variability (The Framingham Heart Study). Am J Cardiol 2000;86: 309–312. 4. Vinik AI, Erbas T. Recognizing and treating diabetic autonomic neuropathy. Clev Clin J Med 2001;68:928– 944. 5. Ziegler D, Zentai C, Perz S, et al. Selective contribution of diabetes and other cardiovascular risk factors to cardiac autonomic dysfunction in the general population. Exp Clin Endocrinol Diabetes 2006;114:153–159. 6. Gottsa¨ter A, Ahlgren AR, Taimour S, et al. Decreased heart rate variability may predict the progression of carotid atherosclerosis in type 2 diabetes. Clin Auton Res 2006;16: 228–234. 7. May O, Arildsen H. Long-term predictive power of heart rate variability on all-cause mortality in the diabetic population. Acta Diabetol 2011;48:55–59.
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8. Aubert AE, Seps B, Beckers F. Heart rate variability in athletes. Sports Med 2003;33:889–919. 9. Zoppini G, Cacciatori V, Gemma ML, et al. Effect of moderate aerobic exercise on sympatho-vagal balance in type 2 diabetes. Diabet Med 2007;24:370–376. 10. Figueroa A, Baynard T, Fernhall B, et al. Endurance training improves post-exercise cardiac autonomic modulation in obese women with and without type 2 diabetes. Eur J Appl Physiol 2007;100:437–444. 11. Morrato EH, Hill JO, Wyatt HR, et al. Physical activity in U.S. adults with diabetes and at risk for developing diabetes, 2003. Diabetes Care 2008;30:203–209. 12. Nelson KM, Reiber G, Boyko EJ. Diet and exercise among adults with type 2 diabetes. Diabetes Care 2002;25:1722– 1728. 13. Leenders M, Verdijk LB, van der Hoeven L, et al. Patients with type 2 diabetes show a greater decline in muscle mass, muscle strength, and functional capacity with aging. J Am Med Dir Assoc 2013;14:585–592. 14. Saper RB, Eisenberg DM, Davis RB, et al. Prevalence and patterns of adult yoga use in the United States: Results of a national survey. Alt Ther Health Med 2004;10: 44–49. 15. Flegal KE, Kishiyama S, Zajdel D, et al. Adherence to yoga and exercise interventions in a 6-month clinical trial. BMC Complement Altern Med 2007;7:37. 16. Dhungel KU, Malhotra V, Sarkar D, et al. Effect of alternate nostril breathing exercise on cardiorespiratory functions. Nepal Med Coll J 2008;10:25–27. 17. Jerath R, Edry JW, Barnes VA, et al. Physiology of long pranayamic breathing: Neural respiratory elements may provide a mechanism that explains how slow deep breathing shifts the autonomic nervous system. Med Hypotheses 2006;67:566–571. 18. Srivastava RD, Jain N, Singhal A. Influence of alternate nostril breathing on cardiorespiratory and autonomic functions in healthy young adults. Indian J Physiol Pharmacol 2005;49:475–483. 19. Pal GK, Velkumary S, Madonmohan. Effect of short-term practice of breathing exercises on autonomic functions in normal human volunteers. Indian J Med Res 2004;120: 115–121. 20. Tarvainen MP, Ranta-Aho PO, Karjalainen PA. An advanced detrending method with application to HRV analysis. IEEE T Bio-Med Eng 2002;49:172–175. 21. Task Force of the European Society of Cardiology, and the North American Society of Pacing, and Electrophysiology. Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Eur Heart J 1996;17: 354–381. 22. Telles S, Nagarathna R, Nagendra HR. Breathing through a particular nostril can alter metabolism and autonomic activities. Indian J Physiol Pharmacol 1994;38:133– 137. 23. Udupa K, Madonmohan, Bhavanani B, et al. Effect of pranayama training on cardiac function in normal young volunteers. Indian J Physiol Pharmacol 2003;47:27–33. 24. Turankar AV, Jain S, Patel SB, et al. Effects of slow breathing exercise on cardiovascular functions, pulmonary functions & galvanic skin resistance in healthy human volunteers: A pilot study. Indian J Med Res 2013;137:916– 921. 25. Raghuraj P, Ramakrishnan AG, Nagendra HR, Telles S. Effect of two selected yogic breathing techniques on heart
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rate variability. Indian J Physiol Pharmacol 1998;42:467– 472. 26. Shannahoff-Khalsa DS, Kennedy B. The effects of unilateral forced nostril breathing on the heart. Int J Neurosci 1993;73:47–60. 27. Raghuraj P, Telles S. Immediate effect of specific nostril manipulating yoga breathing practices on autonomic and respiratory variables. Appl Psychophys Biof 2008;33: 65–75. 28. Pramanik T, Sharma HO, Mishra S, et al. Immediate effect of slow pace bhastrika pranayama on blood pressure and heart rate. J Altern Complement Med 2009;15:293–295.
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29. Wang JYYF, Zhang JW. Structure of slowly adapting pulmonary stretch receptors in the lung periphery. J Appl Physiol 2003;95:385–393.
Address correspondence to: Carmine R. Grieco, PhD Department of Education Glenville State College 212 Louis Bennett Hall Glenville, WV 26351 E-mail: [email protected]
Acute Effect of Breathing Exercises on Heart Rate Variability in Type 2 Diabetes: A Pilot Study Carmine R. Grieco, PhD,1 Sheri R. Colberg, PhD,2 C. Thomas Somma, PhD,3 Andrew G. Thompson, MS,4 and Aaron I. Vinik, MD, PhD 5
Abstract
Background: Type 2 diabetes (T2D) is associated with autonomic nervous system damage resulting in reduced heart rate variability (HRV). Limited evidence suggests yogic breathing exercises may improve indices of HRV. Purpose: The purpose of this study was to evaluate the effect of two commonly used yogic breathing exercises on HRV in T2D versus an age-matched, normoglycemic (CON) population. Methods: Twelve (12) subjects with T2D (7 female, 5 male; 54.9 – 7.4 years) and 14 CON subjects (12 female, 2 male; 54.7 – 6.8 years) participated in a breathing protocol consisting of two 10-min bouts of randomly assigned uni-nostril breathing (UNB). UNB bouts were preceded and followed by 5-min periods of dual-nostril paced breathing (PB). HRV was measured by standard deviation of normal-to-normal consecutive heartbeats (SDNN), square root of the mean squared differences in successive normal heartbeats (RMSSD), and total spectral power (TP). All data (except instantaneous heart rate) were log transformed to improve normality. Within-group comparisons were analyzed using analysis of variance with repeated measures, whereas betweengroup comparisons were analyzed using independent-samples t-test. Results: Between-groups comparisons revealed significant reductions in all measures of HRV at nearly all time points in T2D compared to CON. Within-group comparison demonstrated no significant effect of UNB or PB on HRV in CON. In the T2D group, however, left UNB significantly reduced mean HR ( - 1.2 bpm, p < 0.05) as well as TP ( p < 0.05). Conclusions: In summary, neither UNB nor PB had an impact upon HRV in a healthy older population and had a minimal impact in T2D.
Introduction
T
he prevalence of type 2 diabetes mellitus (T2D) has reached epidemic proportions in the United States and now represents > 1 out of every 10 adults.1 An additional 29.5% of the adult population has prediabetes, a state characterized by impaired fasting glucose and/or impaired glucose tolerance.1 Furthermore, it is predicted that the number of people with diabetes will nearly double within the next 3 decades.2 Damage to the autonomic nervous system (ANS) is a common complication of T2D and may in fact occur prior to diagnosis.3 ANS damage frequently manifests as autonomic
neuropathy (AN), a serious neurological condition that may have a deleterious effect on any organ of the body.4 A characteristic sign of AN is a reduction in heart rate variability (HRV), measured as the time oscillation between successive heartbeats and representing the input of autonomic control over the cardiac cycle in response to changing physiologic demands. HRV is a measure of the underlying tone or balance between sympathetic and vagal (parasympathetic) inputs, with high variability representing an enhanced adaptive ability and low variability reflecting a diminished capacity. A healthy cardiovascular control system will have a high level of complexity, while an aged or diseased system will show a loss of complexity or variability. In fact, in a study of
1
Department of Education, Glenville State College, Glenville, WV. Human Movement Sciences Department and 3Department of Medical Laboratory and Radiation Sciences, Old Dominion University, Norfolk, VA. 4 Department of Kinesiology, Auburn University, Auburn, AL. 5 Strelitz Diabetes Institute, Eastern Virginia Medical School, Norfolk, VA. 2
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1987 older individuals (55–74 years), Ziegler et al.5 determined that the primary factor predicting decreased HRV was the presence of diabetes. Reduced HRV has also been shown to be an early predictor of macrovascular disease, increasing carotid artery atherosclerosis,6 and all-cause mortality in T2D.7 Higher levels of HRV are associated with increased cardiorespiratory fitness,8 and exercise training has demonstrated an important ability to improve HRV in T2D.9,10 Importantly, though, individuals with T2D are less likely to participate in exercise and adhere to an exercise regimen.11,12 Additionally, a frequent complication of T2D is exercise intolerance and a low functional capacity,13 which contributes to the low exercise participation and adherence rates among individuals with T2D. Therefore, any exercise interventions that have a higher adherence rate than standard exercise programming may play a clinically important role in the treatment of T2D. Yoga is an ancient form of physical and psychologic training that has experienced a surge in popularity in the United States.14 The modern practice of yoga as an exercise therapy typically emphasizes the two disciplines of hatha yoga (physical postures) and pranayama (breathing exercises). Prior studies have demonstrated that hatha and hatha/ pranayama yoga training are viable adjunctive therapies for T2D. Importantly, yoga training is also associated with a higher adherence rate than traditional exercise training.15 Many studies support the concept that yogic breathing exercises, independent of hatha yoga practice, may have an ability to influence cardiovascular control via the ANS. Pranayama is associated with improved autonomic tone, specifically increased parasympathetic (vagal) activity.16 Several studies have also demonstrated significant improvements in cardiovascular variables with pranayama that may be attributable to alterations in autonomic tone.17–19 Nevertheless, only limited data investigating the effect of pranayama on HRV exist. Furthermore, to our knowledge this is the first study specifically investigating the effect of pranayama on HRV in T2D. Pranayama represents a simple, inexpensive, and noninvasive tool that may play a role in improving HRV and, more specifically, parasympathetic tone. Therefore, the purpose of this study was to determine the extent to which two commonly employed yogic breathing techniques (slow, paced breathing [PB] and uni-nostril breathing [UNB]) affect HRV in individuals with T2D. Methods Subjects
Twelve (12) subjects with uncomplicated T2D and 14 normoglycemic subjects participated in this investigation. All individuals with T2D were treated with oral antihyperglycemic drugs and/or lifestyle management (diet and exercise). All subjects were prescreened via a health screening questionnaire to determine eligibility. Exclusionary criteria included congested nasal passages (i.e., common cold or allergies), a deviated septum, congestive heart failure, myocardial infarction, arrhythmia or any cardiovascular event in the previous year, or liver, kidney, or pulmonary disease. The study was approved by the Institutional Review Board and all subjects provided signed informed consent.
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Protocol
Subjects were asked to refrain from eating within 3 hours of testing or consuming any caffeine-containing products prior to testing on the assigned day. Each subject was securely fitted with a Bioharness (Zephyr Technology Corp., Annapolis, MD), worn on the chest similar to a heart rate monitor. After premoistening the electrodes on the Bioharness, which is similar to a standard heart rate monitor and consists of a single Velcro-adjusted strap, it was placed against the skin, under clothing, at the level of the sternum. Participants were positioned in a comfortable chair with their feet flat on the ground and instructed to relax and to speak and move as little as possible prior to receiving detailed verbal instructions regarding the breathing protocol. A laptop computer displaying a breath-pacing program was positioned at eye level to provide both auditory and visual cues for breath pacing (E-Z Air Plus, Thought Technology Ltd., West Chazy, NY). For the UNB portion of the protocol, the subjects were instructed to use the contralateral hand to depress and seal off the assigned nostril by placing a single finger (the ring finger) over the nasal vestibule and depressing the tip of the finger until the cessation of air flow was confirmed. Briefly, the breathing protocol consisted sequentially of 5 minutes of spontaneous breathing (nonpaced) (Baseline 1); 2 minutes of spontaneous breathing while standing in place (Stand 1); 5 minutes of paced breathing at a rate of 6 breaths per minutes (Baseline 2); 10 minutes of randomly assigned UNB (UNB1); 5 minutes of paced breathing (Baseline 3); 10 minutes of UNB (opposite nostril) (UNB2); and 2 minutes of paced breathing while standing in place. The slow, paced breathing portion of the protocol was adjusted so each inhale was 4 seconds and each exhale was 6 seconds in duration. The entire breathing protocol lasted 39 minutes. Heart rate variability
HRV data were recorded on a Bioharness collecting at a sampling rate of 250 Hz. The data were then exported as a text file to the HRV analysis software program Kubios HRV 2.0 (Biosignal Analysis and Medical Imaging Group, Department of Physics, University of Kuopio, Finland). Data were visually inspected on a computer monitor to minimize presence of artifact. Detrending of raw data was performed according to Tarvainen et al.,20 and power frequency analysis was performed using a fast Fourier transform with Welch’s periodogram (256s window with 50% overlap). Time domain HRV measurements included mean RR interval, standard deviation of the normal-to-normal consecutive heartbeats (SDNN), and square root of the mean squared differences of successive normal heartbeats (RMSSD). The SDNN is a global measure of variability, while the RMSSD reflects only the vagal influence.21 Frequency domain measurements included total power (TP), presented as absolute power (ms2). TP is considered a marker of total variance.21 Statistics
Data analyses were performed with PASW 17.0 (SPSS, Chicago, IL). As the HRV data were not normally distributed, all of them were logarithmically transformed prior to analysis to improve normality (with the exception of
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Table 1. Log-Transformed Time and Frequency Domain Measurements of Heart Rate Variability (Mean – Standard Error of Mean) Mean HR
Baseline First Stand Baseline 2 LNB Baseline 3 RNB Last Stand Overall
SDNN
Total power (ms2)
RMSSD
CON
T2D
CON
T2D
CON
T2D
CON
T2D
69.7 – 3.43 75.3 – 2.5 67.0 – 2.4 67.4 – 2.2 67.5 – 1.8 67.7 – 2.0 71.4 – 1.9 68.5 – 2.4
73.7 – 4.01 80.1 – 4.1 72.0 – 3.5 70.1 – 2.8{ 70.1 – 2.9 70.9 – 3.1 79.1 – 3.4* 71.3 – 2.9
1.91 – 0.10 2.00 – 0.13 2.06 – 0.08 1.96 – 0.08 2.00 – 0.08 1.94 – 0.08 2.08 – 0.10 2.03 – 0.07
1.64 – 0.33 1.80 – 0.10 1.72 – 0.10* 1.60 – 0.20* 1.63 – 0.07* 1.63 – 0.08* 1.73 – 0.10* 1.76 – 0.06*
1.92 – 0.12 1.87 – 0.15 2.01 – 0.11 1.89 – 0.11 1.93 – 0.10 1.88 – 0.10 2.04 – 0.11 1.97 – 0.09
1.53 – 0.42* 1.58 – 0.15 1.62 – 0.12* 1.42 – 0.07* 1.47 – 0.08* 1.45 – 0.09* 1.53 – 0.14* 1.58 – 0.08*
3.67 – 0.26 3.66 – 0.32 3.92 – 0.18 3.86 – 0.17 3.95 – 0.18 3.87 – 0.21 3.95 – 0.23 3.99 – 0.19
3.07 – 0.21 3.08 – 0.24 3.30 – 0.22 3.07 – 0.12{ 3.21 – 0.13 3.17 – 0.17* 3.22 – 0.20* 3.41 – 0.13*
*Significant difference vs. CON ( p < 0.05). { Significant difference vs. Overall Mean HR within T2D ( p < 0.05). { Significant difference vs. Last Stand ( p < 0.05). SDNN, standard deviation of the normal-to-normal consecutive heartbeats; RMSSD, square root of the mean squared differences of successive normal heartbeats; CON, control group; T2D, type 2 diabetes; RNB, right-nostril breathing; LNB, left nostril breathing; HR, heart rate.
Baseline RMSSD in the T2D group was significantly lower than CON ( p = 0.03). Baseline 2 SDNN and RMSSD
were significantly lower in T2D compared to CON ( p = 0.01 and p = 0.02, respectively) (Table 1). Left-nostril breathing (LNB) SDNN, RMSSD, and TP were significantly lower in T2D compared to CON ( p = 0.001, p = 0.002, and p = 0.001, respectively) (Fig. 1). Baseline 2 SDNN and RMSSD were significantly lower in T2D than CON ( p = 0.003 and p = 0.002, respectively). Right-nostril breathing (RNB) SDNN, RMSSD, and TP were significantly lower in T2D compared to CON ( p = 0.01, p = 0.004, and p = 0.01, respectively). Baseline 3 measurements of SDNN and RMSSD were significantly lower in the T2D group ( p < 0.05) (Fig. 2). Last Stand SDNN, RMSSD, and TP were significantly lower in T2D than in CON ( p = 0.02, p = 0.007, and p = 0.02, respectively). Mean HR during Last Stand was significantly higher in the T2D group (7.7 bpm, p < 0.05) (Fig. 3). Overall SDNN, RMSSD, and TP were significantly lower in T2D than in CON ( p = 0.009, p = 0.005, and p = 0.02, respectively). See Figures 4, 5, and 6 for full protocol comparison of SDNN, RMSSD, and TP.
FIG. 1. Log-transformed standard deviation of the normalto-normal consecutive heartbeats (SDNN) and square root of the mean squared differences of successive normal heartbeats (RMSSD) values during left-nostril breathing in type 2 diabetes (T2D) versus control (CON) subjects. *Significantly less than CON group ( p < 0.05).
FIG. 2. Mean heart rate during Stand 2 comparing subjects with T2D to CON subjects. *Significantly higher than CON group ( p < 0.05).
instantaneous heart rate data). Within-group comparisons were analyzed using analysis of variance with repeated measures on eight time points (Baseline 1, Stand 1, Baseline 2, UNB 1, Baseline 3, UNB 2, Stand 2, and Overall). Betweengroup comparisons were analyzed using independent samples t-tests. Results Subjects
There was no significant difference in age between the T2D group (7 female, 5 male; 54.9 – 7.4 years) and control group (CON) (12 female, 2 male; 54.7 – 6.8 years). The average length of diagnosed diabetes within the T2D group was 8.4 – 6.2 years. Between groups
BREATHING AND SYMPATHOVAGAL BALANCE IN DIABETES
FIG. 3. Log-transformed SDNN and RMSSD during Baseline 3 comparing the T2D versus CON groups. *Significantly less than CON group ( p < 0.05). Within groups
In the T2D group, the LNB protocol resulted in a significantly lower mean heart rate (-1.2 bpm, p = 0.014) in comparison to the overall protocol measures (Fig. 7). The LNB also resulted in a significant decrease in TP compared to Last Stand (-0.15, p < 0.05). There were no other significant interactions within the CON or T2D groups. Discussion
The purpose of this investigation was to examine the acute effect of two common styles of yogic breathing exercises on autonomic tone in individuals with T2D and age-matched controls. Our findings indicated two primary results: (1) neither UNB nor PB had any effect on HRV within an older (54.7 – 6.8 years) normoglycemic group, and (2) the effect within the T2D group was minimal, resulting in a small, but significant, decrease in HR during LNB in comparison to overall HR and a significant decrease in TP during LNB in comparison to the Last Stand. A betweengroups comparison demonstrated significant reductions in
FIG. 4. Comparison of SDNN between CON and T2D groups across 39-minute breathing protocol. *Significantly less than CON group ( p < 0.05). LNB, left-nostril breathing; RNB, right-nostril breathing.
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FIG. 5. Comparison of RMSSD between CON and T2D groups across 39-minute breathing protocol. *Significantly less than CON group ( p < 0.05).
nearly all measures of HRV in the T2D individuals compared to the CON group, which supports previous research showing reduced HRV in T2D. The results of the present study, which investigated the acute effect of pranayama, are in opposition to several previous training studies that have demonstrated a long-term effect of pranayama upon indices of cardiovascular and autonomic-related control in predominantly young and healthy populations. For example, an early study by Telles et al.22 found that 4 weeks of daily LNB significantly increased galvanic skin resistance, indicating a reduction in sympathetic outflow to the sweat glands in healthy, young males. Similarly, Pal et al.19 found that 1 hour of daily slowbreathing pranayama significantly decreased resting HR and HR response to standing in healthy, young males. Likewise, Udupa et al.23 demonstrated that 3 months of pranayama training (20 minutes per day, 5 days per week) significantly lowered resting HR among adolescent boys in comparison to a control group. More recently, Turankar et al.24 showed
FIG. 6. Comparison of total power between CON and T2D groups across 39-minute breathing protocol. *Significantly less than CON group ( p < 0.05). {Significantly different from Last Stand ( p < 0.05).
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FIG. 7. Mean heart rate (HR) in T2D subjects during the LNB compared to the overall mean HR through the entire breathing protocol. *Significantly less than overall mean HR ( p < 0.05).
that as little as 7 days of pranayama training may reduce a marker of sympathetic nervous system excitation (galvanic skin response). Most prior investigations, however, differ from the present one in several important ways, which may help to explain the difference in outcomes: (1) they included training interventions that lasted from 7 days up to 3 months; (2) study populations were typically young, healthy, and male; (3) in several studies, pranayama training is used concurrently with other modalities (i.e., the physical training of hatha yoga and/or the mental training or meditation, which is commonly called dharana or dhyana); (4) frequently the study population has a prior history of pranayama training; and (5) importantly, few studies measured HRV directly, but rather used a surrogate measure of autonomic function (e.g., resting heart rate or blood pressure). Nevertheless, studies involving the chronic effect of pranayama training have provided consistently positive results. While the evidence supporting a training effect of pranayama on autonomic function or surrogate measures of autonomic function is substantial, fewer studies have demonstrated an acute effect. Additionally, such results have been equivocal and inconsistent. For example, an investigation of the acute effect of a single bout of 15 minutes of alternate-nostril breathing (breathing through right and left nostril alternately) in young (25.6 years), healthy male subjects found no significant effect upon HRV.25 In contrast, Shannahoff-Khalsa and Kennedy26 found that a single bout of alternate-nostril breathing conducted for 15 minutes significantly altered HR, with left-nostril breathing decreasing and right-nostril breathing increasing resting HR in older (45.1 years) experienced pranayama practitioners. In one of the few published studies measuring parameters of HRV, Raghuraj and Telles27 recruited 21 young, healthy male volunteers with previous pranayama training. Subjects participated in a protocol that involved 7.5-minute epochs of right-nostril, left-nostril, and alternate-nostril breathing. Right and left nostril breathing had no significant effect upon HRV. Alternate-nostril breathing, however, significantly increased low-frequency power (a metric of sympathetic drive) while simultaneously decreasing high-frequency power (a metric of vagal drive). Similar to the present investigation, our 10-minute epochs of RNB and LNB demonstrated no
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effect upon HRV in older, but normoglycemic, subjects. Contrarily, the T2D group showed a reduction in total power during LNB. Given that sympathetic activation typically results in a reduction of total power, this provides some evidence of sympatho-excitation with LNB in a T2D population. Perhaps the best evidence linking the acute effect of yogic breathing exercises to surrogate measures of autonomic function was a study by Pramanik et al.28 Using a pharmaceutical blockade of parasympathetic stimulation, researchers compared the effect of 5 minutes of slow pranayama on resting heart rate and blood pressure among 39 young participants (an additional 10 subjects received the parasympathetic nervous system (PNS) blockade 30 minutes prior to pranayama). Results indicated significant reductions in diastolic and systolic blood pressure in the group without PNS blockade, and no change within the PNS blockade group. This mediation of resting blood pressure is suggestive of an increase in vagal outflow. There was, however, no direct measurement of HRV. The inconsistency within acute studies is likely a result of different methodological approaches, which influence the potential mechanism through which pranayama exerts it autonomic-modifying effect. While there is no clear consensus on how pranayama works, it has been hypothesized that the autonomic nervous system is functionally reset through stimulation of slowly adapting pulmonary stretch receptors (SAR) and hyperpolarization of fibroblasts located within connective tissue found within the lungs.17 Located within smooth muscle of the airways, the SARs, a class of pulmonary vagal receptor,29 continuously gauge tension within the elastic components of the tracheobronchial tree. The structure and function of SARs remains controversial, however. SARs have been found to play a role in systemic vascular tone and heart rate,17 potentially explaining the greater effect noted in training studies as opposed to acute studies. The consistent modification of cardiovascular and autonomic-related variables demonstrated in training studies and the equivocal findings of acute studies suggests a potential ‘‘threshold’’ effect of vagal afferents (i.e., SARs). If the threshold is met, through successive periods of training, vagal outflow is enhanced; anything below the threshold, however, does not alter vagal afferent activity. Further clarification of the interplay between the autonomic nervous system and afferent lung receptors will be needed before the potential mechanism of action underlying pranayama may be elucidated. To our knowledge, this is the first study that has investigated the effect (either acute or chronic) of yogic breathing exercises on HRV in a T2D population. We originally hypothesized that an acute bout of paced and UNB pranayama would manifest as changes in HRV in both normoglycemic and T2D groups, with greater alterations observed in the T2D population. The results of the investigation, however, provide only minimal support for our hypothesis. These results are largely in accord with the equivocal findings of other acute studies, but run at odds with the preponderance of training studies. The present investigation does have several limitations and must be viewed in the context of the results of previous research. The divergence of our findings from previous studies may be explained by several factors. Most importantly, it is possible that the small subject population,
BREATHING AND SYMPATHOVAGAL BALANCE IN DIABETES
combined with the relatively large variance of the unadjusted data, resulted in a type II error. Secondly, previous studies have used subject populations that are predominantly young, healthy, male and frequently, have prior pranayama training. In contrast, our subjects were older and predominantly female (73%), with an unequal distribution of female subjects between the two groups. Thirdly, this is the first study, to our knowledge, that has investigated the effect of an acute bout of pranayama in individuals with T2D. Without a more clear understanding of the underlying mechanism of action, it is difficult to predict the effect of differing subject populations on study outcomes. While the potential therapeutic effect of pranayama on autonomic function, especially for individuals with T2D, remains an intriguing prospect, more targeted research is necessary to explore the mechanism(s) of action underlying the autonomic-modifying effect of pranayama. Conclusions
In summary, our data indicate a clinically small, but significant, effect of UNB on resting HR and HRV in a population of older individuals with T2D. Slow, paced breathing and UNB, however, had no impact upon resting HR or HRV in an older, normoglycemic population. Nevertheless, there is a growing body of evidence linking yogic-style breathing exercises with autonomic modulation and cardiovascular control. Given the established association between vagal modulation and cardiovascular complications, and the current popularity of yoga and the relative ease of yogic breathing techniques, further research into the autonomic-modifying effects of pranayama is warranted as this shows some promise as an adjunctive therapy in the treatment of type 2 diabetes. Author Disclosure Statement
No competing financial interests exist. References
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Address correspondence to: Carmine R. Grieco, PhD Department of Education Glenville State College 212 Louis Bennett Hall Glenville, WV 26351 E-mail: [email protected]
