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Autonomic function responses to training: Correlation with body composition changes
Physiology & Behavior 151 (2015) 308–313
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Autonomic function responses to training: Correlation with body composition changes Ye Tian a,⁎, Chuanye Huang b, Zihong He a, Ping Hong a, Jiexiu Zhao a a b
China Institute of Sport Science, Beijing, China Department of Sports Science, Shandong University of Sport, Shandong, China
H I G H L I G H T S • • • •
Exercise training improves vagal activity, body composition and aerobic fitness. Vagal activity changes are associated with fat reduction after aerobic exercise. Correlations are observed between changes of vagal activity and aerobic fitness. Resting heart rate variability changes may predict adaptations to training program.
a r t i c l e
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Article history: Received 15 February 2015 Received in revised form 19 July 2015 Accepted 30 July 2015 Available online 5 August 2015 Keywords: Heart rate variability Body composition Peak oxygen uptake
a b s t r a c t Aim: The causal relation between autonomic function and adiposity is an unresolved issue. Thus, we studied whether resting heart rate variability (HRV) changes could be used to predict changes in body composition after 16 weeks of individualized exercise training. Methods: A total of 117 sedentary overweight/obese adults volunteered to join an intervention group (IN, n = 82) or a control group (CON, n = 35). The intervention group trained for 30–40 min three times a week with an intensity of 85–100% of individual ventilatory threshold (Thvent). At baseline and after a 16-week training period, resting HRV variables, body composition and peak oxygen uptake (VO2peak) were assessed. Results: Compared with CON, exercise training significantly improved HRV and body composition and increased VO2peak (P b 0.05). Significant correlations were observed between changes of HRV variables and body composition indices and VO2peak (P b 0.05). Greater individual changes in HRV in response to exercise training were observed for those with greater total and central fat loss. Conclusion: Individual aerobic-based exercise training was for improving autonomic function and resting HRV responses to aerobic training is a potential indicator for adaptations to exercise training. © 2015 Published by Elsevier Inc.
1. Introduction Heart rate variability (HRV) is a noninvasive method for analyzing autonomic function via assessment of beat-to-beat variations in R–R intervals [1]. Evaluation of autonomic function is of great interest to health professionals—HRV is associated with increased risk of cardiac events and all-cause mortality [2,3]. Thus, we sought to understand whether HRV alterations are pathways through which cardiovascular health can be affected by lifestyle-related risk factors [3]. Obesity/overweight is related to disease risks and increasingly represents a major, worldwide health concern [4]. Increased weight and adiposity is associated with a sedentary lifestyle and dietary excesses and these are often characterized by decreases in HRV [5,6]. For ⁎ Corresponding author at: China Institute of Sport Science, 11 Tiyuguan Road, Dongcheng District, Beijing 100061, China. E-mail address: [email protected] (Y. Tian).
http://dx.doi.org/10.1016/j.physbeh.2015.07.038 0031-9384/© 2015 Published by Elsevier Inc.
example, poor HRV has been associated with greater skinfold thickness, higher body mass index (BMI) level and higher body fat percentages [7–9]. In contrast, weight loss via hypocaloric diets and/or exercise training, has been shown to reverse negative influences of weight gain on autonomic modulation [10–13]. However, such these relationships are unclear due to differences in proxy measures of body composition and require study [14,15]. Understanding how HRV is related to body composition changes elicited by aerobic exercise in overweight/obese subjects may offer insights into cardiovascular risks and help with anti-obesity strategies. At this time, most studies are cross sectional [5, 16] or include obese individuals with chronic diseases [13]. Less is known about how exercise-induced body composition changes HRV, particularly in overweight/obese, sedentary adults. Therefore, we attempted to elucidate the link between autonomic nervous (ANS) activity and body composition after an exercise intervention. Specifically, we studied whether a long-term aerobic exercise could change autonomic tone and whether this was related to body
Y. Tian et al. / Physiology & Behavior 151 (2015) 308–313
composition variables in a population of healthy overweight/obese adults. A positive result would support the feasibility of introducing non-invasive autonomic cardiovascular regulation assessment as a means to monitor the adaptation to exercise in overweight/obese adults.
2. Methods 2.1. Subjects Obese or overweight men and women (N = 117) aged 20–59 years with body mass indices (BMI) N25 kg·m−2 were recruited via public advertisement. Subjects self-reported a sedentary lifestyle for a minimum of 12 months before enrolling in this study. Pre-participation health screening was performed in accordance with the American College of Sports Medicine [17]. Subjects were excluded if they had any clinical sign of cardiovascular diseases, neurological or other overt chronic diseases, or current medication use. Eligible subjects volunteered to join an intervention group (IN, n = 82) or a control group (CON, n = 35). Premenopausal female subjects were studied in the first 10 days of the menstrual cycle. Table 1 depicts the IN and CON groups before and after a 16-week training period. Subjects provided written informed consent and the protocol was approved by the local Ethical Committee and was conducted according to Declaration of Helsinki.
2.2. Study design Subjects initially underwent graded exercise testing in a controlled laboratory setting to determine peak oxygen uptake (VO2peak) and heart rate (HR) at ventilatory threshold (Thvent). Thereafter, the intervention group performed 16 weeks of aerobic exercise at a specified intensity based on their individual Thvent, whereas the CON group was asked to maintain their current lifestyles. During the study period, all subjects were instructed to maintain their dietary patterns. Measurements were made in each subject at baseline and 48 h after the last training session. Anthropometry, resting HRV, and a cardiorespiratory fitness tests were conducted at the same time of the day for each subject. Prior to test, each subject was requested to abstain from caffeine or alcohol consumption and strenuous exercise for 24 h. All subjects consumed their last meal at least 2 h before testing.
2.3. Anthropometrics Subjects wore light clothing with shoes and height and weight were measured using a stadiometer and an electronic scale. BMI was calculated as weight (kg) divided by height squared (m2). Waist circumference was measured from midway between the lower rib margin and the iliac crest. Hip circumference was measured at the level of trochanter major and the waist-to-hip ratio was calculated. Body composition was measured with dual-energy X-ray absorptiometry (GE-Lunar Radiation Corp., Madison, WI) with subjects in the supine position.
Table 1 Subject data before and after the 16-week training period. IN, n = 82
Male/female Age (yr) Height (cm) Weight (kg) a
CON, n = 35
Baseline
16-weeks
Baseline
16-weeks
49/33 42.5 ± 9.9 167.4 ± 8.1 76.3 ± 9.4
49/33 – – 74.6 ± 9.7a
17/18 41.7 ± 10.8 165.4 ± 7.4 76.0 ± 8.2
17/18 – – 77.2 ± 8.6a
P b 0.05,significantly different than baseline value within group.
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2.4. Maximal exercise test The VO2peak and Thvent were measured with a graded exercise test on a cycle ergometer (Ergoline 100, Ergoline, Bitz, Germany). Briefly, the initial workload of 25 W for male and 20 W for female was increased by 25 W and 20 W every 2 min, respectively. The test ended when the subject was no longer able to maintain the fixed pedaling frequency (60 rpm), despite maximal voluntary effort and strong verbal encouragements. HR was recorded every 5 s with a polar HR monitor (RS400, Polar Electro, Kempele, Finland). Respiratory gas exchange was measured breath-by-breath using an automated portable metabolic system (MetaMax 3B, Cortex, Biophysik, Germany), which was calibrated before each test according to the manufacturer's instructions. VO2peak was defined as the highest 30-s average value of VO2. As previously described [18], Thvent was defined as the point at which minute ventilation (VE) increased in a nonlinear fashion or when the ventilatory equivalent for O2 began to rise without a concomitant rise in the ventilator equivalent for CO2. The Thvent and the corresponding HR were identified by two independent and blinded test administrators. 2.5. R–R interval recordings and analysis R–R intervals were recorded using a heart-rate monitor at an accuracy of 1 ms (RS800, Polar Electro, Kempele, Finland) in the lying position for 10 min. This device has been considered a reliable and validity method of capture and analysis inter-beat variability [19,20]. Recordings were performed between 8:00 AM and 9:00 AM to avoid possible circadian influences on autonomic function. Prior to the recording, subjects rested comfortably supine for at least 10 min in a quiet, dimly lit room maintained at a constant temperature. Subjects were overnight fasted and refrained from any strenuous exercise and alcohol consumption for 24 h before the measurement. Normal breathing frequency and tidal volume were maintained during the testing. The recorded R–R data were transferred to a personal computer and analyzed with Polar professional training software (ProTrainer 5™, Polar Electro, Kempele, Finland). All ectopic beats were filtered and corrected. HRV variables were calculated during the last 5 min of the 10-min supine R–R interval recordings according to current guidelines [1]. Time-domain parameters included the standard deviation of R to R intervals (SDNN) and squared differences between adjacent normal N–N intervals (RMSSD). Frequency-domain parameters were derived from the power spectral density data of R–R interval signals using auto regression techniques. Total power (TP 0–0.4 Hz), high frequency (HF 0.15–0.4 Hz) and low frequency (LF 0.04–0.15 Hz) spectral power were obtained. Among these parameters, the RMSSD and HF represent vagal activity, LF power is regarded to reflect predominantly sympathetic and, to lesser extent vagal activity. SDNN and TP power reflect global modulation. 2.6. Training interventions The IN subjects participated in a progressive aerobic exercise (running or cycling) program for 16 weeks (Table 2). Training sessions were carried out 3 days/week (40–60 min/session). Exercise intensities were increased progressively from 85% up to 100% of individual Thvent and closely monitored by a personal HR monitors (Polar T31, Polar Electo, Kempele, Finland) and work rate was adjusted to maintain target HR. The aerobic training protocol was planned on the basis of the recommendations of American College of Sports Medicine [21]. All training sessions were carefully supervised by trained technicians. 2.7. Statistical analyses Statistical analyses were performed using the Statistical Package for the Social Sciences version 17.0 (SPSS Inc., Chicago, IL). Normality was
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Table 2 Template of 16-week training program. Training period
Warm-up Exercise Cool down
Weeks 1–4
Weeks 5–8
Weeks 9–12
Weeks 13–16
Moderate intensity exercise, 10 min 85% of Thvent, 3 sections/week, 30
Moderate intensity exercise, 10 min 85% of Thvent, 3 sections/week, 40
Moderate intensity exercise, 10 min 95% of Thvent, 3 sections/week, 40
Moderate intensity exercise, 10 min 100% of Thvent, 3 sections/week, 40
min/section min/section min/section min/section Self-selected intensity exercise, 10 min Self-selected intensity exercise, 10 min Self-selected intensity exercise, 10 min Self-selected intensity exercise, 10 min
Thvent, ventilatory threshold.
tested using the Shapiro–Wilk normality tests. Skewed distributions of HRV variables were normalized by natural logarithms (ln). Two-way ANOVA (group × time) with repeated measures was used to examine the significance of changes in variables after exercise. Post hoc comparisons were made by Bonferroni tests. Standardized effects sizes (ES) were also calculated with the following threshold values: ≤0.2 trivial, N0.2 small, N0.6 moderate, and N 1.2 large [22]. Correlations among changes (△) of HRV variables, and improvements in body composition and performance were performed using Pearson correlation. Stepwise linear regression procedures were also performed to determine the extent to which the independent variables could explain the variation in each of the autonomic measures. All data are presented as means ± SD. Statistical significance was defined as P b 0.05. 3. Results All subjects completed the 16-week experimental study. No baseline differences were observed in age, body weight, height, BMI and aerobic fitness between groups prior to the intervention (P N 0.05, Table 1). The body composition, heart rate variability and aerobic fitness outcomes following exercise training are illustrated in Table 1 and Table 3. There were significant reductions (P b 0.05) in body weight (ES = 0.19, trivial), BMI (ES = 0.36, small), body fat mass (ES = 0.37, small), body fat percentage (ES = 0.30, small), trunk fat mass (ES = 0.34, small), trunk fat percentage (ES = 0.30, small), hip circumference (ES = 0.27, small) and waist circumference (ES = 0.32, small) in response to training. However, waist-to-hip ratio (ES = 0.00, trivial, P N 0.05) was Table 3 Changes in body composition, heart rate variability and aerobic fitness after intervention. IN
Body mass index (kg·m−2) Body fat mass (kg) Body fat percentage (%) Trunk fat mass (kg) Trunk fat percentage (%) Waist circumference (cm) Hip circumference (cm) Waist-to-hip ratio SDNN (ln ms) RSSMD (ln ms) TP (ln ms2) HF (ln ms2) LF (ln ms2) VO2peak (l·min−1) VO2peak (ml·kg−1·min−1)
CON
Baseline
16-weeks
27.2 ± 1.7
26.5 ± 2.1a,b
Baseline 27.8 ± 2.1
28.2 ± 2.2a
24.7 ± 5.0 33.2 ± 6.8
22.8 ± 5.2a,b 31.1 ± 7.2a,b
25.3 ± 5.3 34.1 ± 7.6
25.5 ± 5.9 34.3 ± 7.8
15.4 ± 3.1 40.1 ± 6.1†
14.3 ± 3.2a 37.8 ± 6.5a
14.7 ± 3.4 38.2 ± 7.11
14.8 ± 3.5 38.3 ± 7.6
92.7 ± 7.0
90.4 ± 7.4a,b
93.0 ± 7.3
94.0 ± 7.0
99.3 ± 4.4
97.8 ± 6.6a,b
100.6 ± 4.4
100.5 ± 5.1
0.93 ± 0.06 3.62 ± 0.29 3.16 ± 0.46 7.35 ± 0.78 5.28 ± 1.01 5.74 ± 0.85 2.06 ± 0.56 26.8 ± 5.5
0.93 ± 0.09 3.78 ± 0.46a,b 3.48 ± 0.59a,b 7.69 ± 0.94a,b 5.84 ± 1.20a,b 5.97 ± 1.12* 2.29 ± 0.66a,b 29.9 ± 6.8a,b
0.92 ± 0.06 3.58 ± 0.34 3.38 ± 0.66 7.28 ± 0.83 5.27 ± 0.93 5.68 ± 0.92 1.92 ± 0.46 25.3 ± 4.9
16-weeks
0.94 ± 0.07a 3.49 ± 0.40a 3.27 ± 0.63 7.04 ± 0.87a 5.20 ± 1.08 5.44 ± 0.79a 1.90 ± 0.44 24.6 ± 4.6
RMSSD, root mean square of successive differences. HF, high frequency spectral power. Ln, natural logarithm. VO2peak, peak oxygen uptake. a P b 0.05, significantly different than baseline value within group. b P b 0.05, significantly different from CON at the same time point.
maintained across the intervention period (Table 3). For the control group, no significant changes in body composition parameters were observed at the follow-up examination (P N 0.05), except for body weight (ES = 0.14, trivial, P b 0.05), BMI (ES = 0.19, trivial, P b 0.05) and waistto-hip ratio (ES = 0.30, small, P b 0.05). The exercising group had greater SDNN (ES = 0.42, small), RSSMD (ES = 0.68, moderate), TP (ES = 0.39, small), HF (ES = 0.50, small) and LF (ES = 0.23, small), after the intervention (P b 0.05). For CON group, significant decreases in SDNN (ES = 0.24, small), TP (ES = 0.28, small) and LF (ES = 0.33, small) were demonstrated across the intervention period, except for RSSMD and HF (P N 0.05, Table 3).In addition, compared with baseline, training increased relative VO2peak by 11.6% in IN (ES = 0.48, small, P b 0.05). Control subjects had no significant change in VO2peak from baseline to 16 weeks (P N 0.05). Table 4 depicts correlation coefficients (r) for changes between heart rate variability and body composition variables and aerobic fitness (n = 117). Subjects with greater individual changes in vagal-related HRV variables had more changes in body/trunk fat and a greater increase in absolute VO2peak over the intervention period (Fig. 1). The results of the stepwise regression procedures revealed that changes in trunk fat percentage, waist circumference and absolute VO2max accounted for the variance in RSSMD ln (R2 = 0.557, P b 0.05). For HF ln, the change in trunk fat mass and body weight accounted for the variance in HF ln (R2 = 0.417, P b 0.05). For TP ln, the BMI accounted for the variance in TP ln (R2 = 0.132, P b 0.05). No other variable added statistical significance (P N 0.05) to the regression models and therefore was removed from the models. 4. Discussion The main findings of the present study demonstrate that autonomic function improves with fat loss after an aerobic training program in overweight/obese adults. Changes in resting HRV were significantly related to later body composition changes. Moreover, the subjects with more vagalrelated HRV changes had greater enhancement of physical fitness.
Table 4 Correlation coefficients (r) of changes between heart rate variability and selected body composition variables and aerobic fitness after adjustment on age (n = 117).
△Body weight (kg) △Body fat mass (kg) △Body fat percentage (%) △Trunk fat mass (kg) △Trunk fat percentage (%) △Waist circumference (cm) △Waist-to-hip ratio △Body mass index (kg·m−2) △VO2 peak (l·min−1) △VO2 peak (ml·kg−1·min−1)
△SDNN ln ms
△RSSMD △TP ln ms ln ms2
△HF ln ms2
△LF ln ms2
−0.204a −0.143 −0.196a −0.152 −0.229a −0.051 −0.020 −0.186a
−0.420a −0.362a −0.406a −0.364a −0.436a −0.258a −0.167 −0.409a
−0.341a −0.172 −0.164 −0.178 −0.198a −0.201a −0.100 −0.361a
−0.369a −0.311a −0.300a −0.344a −0.348a −0.092 −0.086 −0.353a
−0.048 −0.131 −0.092 −0.030 −0.027 −0.061 −0.091 −0.032
0.083 0.240a
0.437a 0.424a
0.155 0.211a
0.296a 0.269a
0.125 0.194
△ = 16 week value-baseline value, VO2 peak peak oxygen uptake. a P b 0.05.
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Fig. 1. Association between individual training response (changes in selected body composition parameters and relative VO2peak) and cardiac vagal activity changes ● IN group, ○ CON group.
Overweight or obesity per se is associated with an increased risk of cardiovascular diseases, and previous studies suggest that cardiac autonomic control of heart rate is blunted due to excess fat and weight gain [23–25]. Our findings indicate that greater fat loss in individuals with more vagal-related HRV variable improvements, supporting previous findings in overweight/obese individuals, which reveal that depressed HRV could be reversed after dietary weight loss interventions, exercise training or combinations of both [10–12,26]. It is believed that impaired autonomic control of heart rate is associated with increased risk of cardiovascular mortality and that improvements in HRV variables are independent protectors against sudden death [2]. Moreover, consistent with previous multiple cross-sectional studies [27,28], our data demonstrate that central adiposity influences autonomic function. Indeed, we found that subjects with more central fat loss (measured by waist circumference and trunk fat percentage) had more improvement in HRV. In this context, perhaps, more favorable HRV profiles may be seen later with weight control as the proportion of fat loss increases.
Although the influence of weight status on HRV has been studied extensively [27,29], the link between weight loss and beneficial alterations in cardiac autonomic function is unclear. For example, in one study, data did not reveal significant changes in HRV variables after weight loss [30]. In another study, continuous endurance training with moderate intensity did not influence resting HRV in obese women in the absence of fat loss [31]. Of note, our subjects on a progressively increased (lowto-moderate) intensity training regimen experienced significant changes. Unlike previous findings [32], our current study clearly demonstrated significant correlations between changes in HRV and fat loss after aerobic exercise. Methodological differences in HRV recording and proxy measures of body composition may partly explain inconsistencies between our results and those of previous studies. Even so, our observations indicate that the effect of training on autonomic function might be influenced by body fat loss in addition to exercise duration and intensity. To our knowledge, however, the mechanisms by which fat loss favors increased autonomic function are still unclear. Alterations
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of several potential factors might be involved, such as insulin resistance [33], leptin [34] and inflammation [35]. How improvements in autonomic function occur after fat loss warrants future studies. Large inter-individual differences in vagal modulation changes with fat loss were observed in our subjects (Fig. 1) and these data extended and clarified an earlier study [26]. A previous cross-sectional HRV study revealed worse profiles for women with upper-body rather than lower-body obesity and with visceral rather that subcutaneous obesity [36]. Another study confirmed lower parasympathetic and greater sympathetic modulation of HRV in obese girls with higher central fat compared to those with lower central fat [27]. Thus, individual differences in HRV response might be attributed to regional fat distribution [24,28]. These observed changes in vagal-related HRV variables were significantly associated with changes in trunk fat percentage and/or waist circumference further support the aforementioned concept. Although autonomic function appears to be influenced in individuals with central adiposity in our current study, low R2 values revealed that reduced central fat does not fully explain variations in HRV. A prior study suggested that a hypocaloric diet associated with exercise training, in contrast to a hypocaloric diet alone, had more effects on autonomic activity [10]. In our laboratory, correlation procedures were significantly correlated between increased aerobic fitness (VO2peak) and changes in HRV variables. These results were further supported by the stepwise regression procedures, which revealed that changes in absolute VO2peak partially accounted for variation in RMSSD. Our data are consistent with the idea that training improves autonomic function [37,38]. Individual differences in the responsivity of aerobic fitness to exercise training might also be linked to variances in cardiovascular autonomic control and this idea agrees with increasing evidence to suggest that HRV may be useful for predicting individual aerobic fitness in response to training [38]. The subjects studied represented a relatively large BMI range which may offer a better understanding of the link between cardiac autonomic function and body composition. Trends in improved HRV that are associated with reduced obesity observed after aerobic training appear to reinforce the concept of a cardiovascular protection mechanism, and at the same time offered information regarding decreased mortality and morbidity from cardiovascular disease with appropriate lifestyle adaptations. Furthermore, our positive findings will contribute to the ongoing debate concerning non-invasive measurement of HRV for monitoring benefits of exercise interventions for overweight/obese individuals and suggest effective anti-obesity strategies. However, the study has several limitations. Firstly, although men and women were included in both groups, there were no sex-related differences in HRV at baseline or after exercise training. Also, the age range of the subjects was large, and the sample was biased which may affect statistical analysis. Additionally, the HRV was measured during spontaneous breathing at rest is a limitation of this study. Nevertheless, breathing frequency was in the high frequency range (0.15–0.50 Hz) and vagal-related HRV variables during spontaneous and paced breathing did not differ significantly [39]. The limit between high- and low-frequency fields of R–R interval variability in the power spectral analysis has been set [1] so that only breathing frequency of b 9 breaths·min− 1 gives a respiratory peak to the low-frequency field. Therefore, it is unlikely that our training protocol could have decreased the breathing frequency enough to influence the results, even if training is believed to decrease breathing frequency. Finally, this longitudinal study revealed decreased adiposity and increased VO2peak after the intervention. Therefore, the independent influences of body composition and aerobic fitness on autonomic activity are confounded. Future research should identify the distinct influences of both variables and the mechanisms that underlie the relationship between cardiovascular autonomic function and body composition.
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Physiology & Behavior journal homepage: www.elsevier.com/locate/phb
Autonomic function responses to training: Correlation with body composition changes Ye Tian a,⁎, Chuanye Huang b, Zihong He a, Ping Hong a, Jiexiu Zhao a a b
China Institute of Sport Science, Beijing, China Department of Sports Science, Shandong University of Sport, Shandong, China
H I G H L I G H T S • • • •
Exercise training improves vagal activity, body composition and aerobic fitness. Vagal activity changes are associated with fat reduction after aerobic exercise. Correlations are observed between changes of vagal activity and aerobic fitness. Resting heart rate variability changes may predict adaptations to training program.
a r t i c l e
i n f o
Article history: Received 15 February 2015 Received in revised form 19 July 2015 Accepted 30 July 2015 Available online 5 August 2015 Keywords: Heart rate variability Body composition Peak oxygen uptake
a b s t r a c t Aim: The causal relation between autonomic function and adiposity is an unresolved issue. Thus, we studied whether resting heart rate variability (HRV) changes could be used to predict changes in body composition after 16 weeks of individualized exercise training. Methods: A total of 117 sedentary overweight/obese adults volunteered to join an intervention group (IN, n = 82) or a control group (CON, n = 35). The intervention group trained for 30–40 min three times a week with an intensity of 85–100% of individual ventilatory threshold (Thvent). At baseline and after a 16-week training period, resting HRV variables, body composition and peak oxygen uptake (VO2peak) were assessed. Results: Compared with CON, exercise training significantly improved HRV and body composition and increased VO2peak (P b 0.05). Significant correlations were observed between changes of HRV variables and body composition indices and VO2peak (P b 0.05). Greater individual changes in HRV in response to exercise training were observed for those with greater total and central fat loss. Conclusion: Individual aerobic-based exercise training was for improving autonomic function and resting HRV responses to aerobic training is a potential indicator for adaptations to exercise training. © 2015 Published by Elsevier Inc.
1. Introduction Heart rate variability (HRV) is a noninvasive method for analyzing autonomic function via assessment of beat-to-beat variations in R–R intervals [1]. Evaluation of autonomic function is of great interest to health professionals—HRV is associated with increased risk of cardiac events and all-cause mortality [2,3]. Thus, we sought to understand whether HRV alterations are pathways through which cardiovascular health can be affected by lifestyle-related risk factors [3]. Obesity/overweight is related to disease risks and increasingly represents a major, worldwide health concern [4]. Increased weight and adiposity is associated with a sedentary lifestyle and dietary excesses and these are often characterized by decreases in HRV [5,6]. For ⁎ Corresponding author at: China Institute of Sport Science, 11 Tiyuguan Road, Dongcheng District, Beijing 100061, China. E-mail address: [email protected] (Y. Tian).
http://dx.doi.org/10.1016/j.physbeh.2015.07.038 0031-9384/© 2015 Published by Elsevier Inc.
example, poor HRV has been associated with greater skinfold thickness, higher body mass index (BMI) level and higher body fat percentages [7–9]. In contrast, weight loss via hypocaloric diets and/or exercise training, has been shown to reverse negative influences of weight gain on autonomic modulation [10–13]. However, such these relationships are unclear due to differences in proxy measures of body composition and require study [14,15]. Understanding how HRV is related to body composition changes elicited by aerobic exercise in overweight/obese subjects may offer insights into cardiovascular risks and help with anti-obesity strategies. At this time, most studies are cross sectional [5, 16] or include obese individuals with chronic diseases [13]. Less is known about how exercise-induced body composition changes HRV, particularly in overweight/obese, sedentary adults. Therefore, we attempted to elucidate the link between autonomic nervous (ANS) activity and body composition after an exercise intervention. Specifically, we studied whether a long-term aerobic exercise could change autonomic tone and whether this was related to body
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composition variables in a population of healthy overweight/obese adults. A positive result would support the feasibility of introducing non-invasive autonomic cardiovascular regulation assessment as a means to monitor the adaptation to exercise in overweight/obese adults.
2. Methods 2.1. Subjects Obese or overweight men and women (N = 117) aged 20–59 years with body mass indices (BMI) N25 kg·m−2 were recruited via public advertisement. Subjects self-reported a sedentary lifestyle for a minimum of 12 months before enrolling in this study. Pre-participation health screening was performed in accordance with the American College of Sports Medicine [17]. Subjects were excluded if they had any clinical sign of cardiovascular diseases, neurological or other overt chronic diseases, or current medication use. Eligible subjects volunteered to join an intervention group (IN, n = 82) or a control group (CON, n = 35). Premenopausal female subjects were studied in the first 10 days of the menstrual cycle. Table 1 depicts the IN and CON groups before and after a 16-week training period. Subjects provided written informed consent and the protocol was approved by the local Ethical Committee and was conducted according to Declaration of Helsinki.
2.2. Study design Subjects initially underwent graded exercise testing in a controlled laboratory setting to determine peak oxygen uptake (VO2peak) and heart rate (HR) at ventilatory threshold (Thvent). Thereafter, the intervention group performed 16 weeks of aerobic exercise at a specified intensity based on their individual Thvent, whereas the CON group was asked to maintain their current lifestyles. During the study period, all subjects were instructed to maintain their dietary patterns. Measurements were made in each subject at baseline and 48 h after the last training session. Anthropometry, resting HRV, and a cardiorespiratory fitness tests were conducted at the same time of the day for each subject. Prior to test, each subject was requested to abstain from caffeine or alcohol consumption and strenuous exercise for 24 h. All subjects consumed their last meal at least 2 h before testing.
2.3. Anthropometrics Subjects wore light clothing with shoes and height and weight were measured using a stadiometer and an electronic scale. BMI was calculated as weight (kg) divided by height squared (m2). Waist circumference was measured from midway between the lower rib margin and the iliac crest. Hip circumference was measured at the level of trochanter major and the waist-to-hip ratio was calculated. Body composition was measured with dual-energy X-ray absorptiometry (GE-Lunar Radiation Corp., Madison, WI) with subjects in the supine position.
Table 1 Subject data before and after the 16-week training period. IN, n = 82
Male/female Age (yr) Height (cm) Weight (kg) a
CON, n = 35
Baseline
16-weeks
Baseline
16-weeks
49/33 42.5 ± 9.9 167.4 ± 8.1 76.3 ± 9.4
49/33 – – 74.6 ± 9.7a
17/18 41.7 ± 10.8 165.4 ± 7.4 76.0 ± 8.2
17/18 – – 77.2 ± 8.6a
P b 0.05,significantly different than baseline value within group.
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2.4. Maximal exercise test The VO2peak and Thvent were measured with a graded exercise test on a cycle ergometer (Ergoline 100, Ergoline, Bitz, Germany). Briefly, the initial workload of 25 W for male and 20 W for female was increased by 25 W and 20 W every 2 min, respectively. The test ended when the subject was no longer able to maintain the fixed pedaling frequency (60 rpm), despite maximal voluntary effort and strong verbal encouragements. HR was recorded every 5 s with a polar HR monitor (RS400, Polar Electro, Kempele, Finland). Respiratory gas exchange was measured breath-by-breath using an automated portable metabolic system (MetaMax 3B, Cortex, Biophysik, Germany), which was calibrated before each test according to the manufacturer's instructions. VO2peak was defined as the highest 30-s average value of VO2. As previously described [18], Thvent was defined as the point at which minute ventilation (VE) increased in a nonlinear fashion or when the ventilatory equivalent for O2 began to rise without a concomitant rise in the ventilator equivalent for CO2. The Thvent and the corresponding HR were identified by two independent and blinded test administrators. 2.5. R–R interval recordings and analysis R–R intervals were recorded using a heart-rate monitor at an accuracy of 1 ms (RS800, Polar Electro, Kempele, Finland) in the lying position for 10 min. This device has been considered a reliable and validity method of capture and analysis inter-beat variability [19,20]. Recordings were performed between 8:00 AM and 9:00 AM to avoid possible circadian influences on autonomic function. Prior to the recording, subjects rested comfortably supine for at least 10 min in a quiet, dimly lit room maintained at a constant temperature. Subjects were overnight fasted and refrained from any strenuous exercise and alcohol consumption for 24 h before the measurement. Normal breathing frequency and tidal volume were maintained during the testing. The recorded R–R data were transferred to a personal computer and analyzed with Polar professional training software (ProTrainer 5™, Polar Electro, Kempele, Finland). All ectopic beats were filtered and corrected. HRV variables were calculated during the last 5 min of the 10-min supine R–R interval recordings according to current guidelines [1]. Time-domain parameters included the standard deviation of R to R intervals (SDNN) and squared differences between adjacent normal N–N intervals (RMSSD). Frequency-domain parameters were derived from the power spectral density data of R–R interval signals using auto regression techniques. Total power (TP 0–0.4 Hz), high frequency (HF 0.15–0.4 Hz) and low frequency (LF 0.04–0.15 Hz) spectral power were obtained. Among these parameters, the RMSSD and HF represent vagal activity, LF power is regarded to reflect predominantly sympathetic and, to lesser extent vagal activity. SDNN and TP power reflect global modulation. 2.6. Training interventions The IN subjects participated in a progressive aerobic exercise (running or cycling) program for 16 weeks (Table 2). Training sessions were carried out 3 days/week (40–60 min/session). Exercise intensities were increased progressively from 85% up to 100% of individual Thvent and closely monitored by a personal HR monitors (Polar T31, Polar Electo, Kempele, Finland) and work rate was adjusted to maintain target HR. The aerobic training protocol was planned on the basis of the recommendations of American College of Sports Medicine [21]. All training sessions were carefully supervised by trained technicians. 2.7. Statistical analyses Statistical analyses were performed using the Statistical Package for the Social Sciences version 17.0 (SPSS Inc., Chicago, IL). Normality was
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Table 2 Template of 16-week training program. Training period
Warm-up Exercise Cool down
Weeks 1–4
Weeks 5–8
Weeks 9–12
Weeks 13–16
Moderate intensity exercise, 10 min 85% of Thvent, 3 sections/week, 30
Moderate intensity exercise, 10 min 85% of Thvent, 3 sections/week, 40
Moderate intensity exercise, 10 min 95% of Thvent, 3 sections/week, 40
Moderate intensity exercise, 10 min 100% of Thvent, 3 sections/week, 40
min/section min/section min/section min/section Self-selected intensity exercise, 10 min Self-selected intensity exercise, 10 min Self-selected intensity exercise, 10 min Self-selected intensity exercise, 10 min
Thvent, ventilatory threshold.
tested using the Shapiro–Wilk normality tests. Skewed distributions of HRV variables were normalized by natural logarithms (ln). Two-way ANOVA (group × time) with repeated measures was used to examine the significance of changes in variables after exercise. Post hoc comparisons were made by Bonferroni tests. Standardized effects sizes (ES) were also calculated with the following threshold values: ≤0.2 trivial, N0.2 small, N0.6 moderate, and N 1.2 large [22]. Correlations among changes (△) of HRV variables, and improvements in body composition and performance were performed using Pearson correlation. Stepwise linear regression procedures were also performed to determine the extent to which the independent variables could explain the variation in each of the autonomic measures. All data are presented as means ± SD. Statistical significance was defined as P b 0.05. 3. Results All subjects completed the 16-week experimental study. No baseline differences were observed in age, body weight, height, BMI and aerobic fitness between groups prior to the intervention (P N 0.05, Table 1). The body composition, heart rate variability and aerobic fitness outcomes following exercise training are illustrated in Table 1 and Table 3. There were significant reductions (P b 0.05) in body weight (ES = 0.19, trivial), BMI (ES = 0.36, small), body fat mass (ES = 0.37, small), body fat percentage (ES = 0.30, small), trunk fat mass (ES = 0.34, small), trunk fat percentage (ES = 0.30, small), hip circumference (ES = 0.27, small) and waist circumference (ES = 0.32, small) in response to training. However, waist-to-hip ratio (ES = 0.00, trivial, P N 0.05) was Table 3 Changes in body composition, heart rate variability and aerobic fitness after intervention. IN
Body mass index (kg·m−2) Body fat mass (kg) Body fat percentage (%) Trunk fat mass (kg) Trunk fat percentage (%) Waist circumference (cm) Hip circumference (cm) Waist-to-hip ratio SDNN (ln ms) RSSMD (ln ms) TP (ln ms2) HF (ln ms2) LF (ln ms2) VO2peak (l·min−1) VO2peak (ml·kg−1·min−1)
CON
Baseline
16-weeks
27.2 ± 1.7
26.5 ± 2.1a,b
Baseline 27.8 ± 2.1
28.2 ± 2.2a
24.7 ± 5.0 33.2 ± 6.8
22.8 ± 5.2a,b 31.1 ± 7.2a,b
25.3 ± 5.3 34.1 ± 7.6
25.5 ± 5.9 34.3 ± 7.8
15.4 ± 3.1 40.1 ± 6.1†
14.3 ± 3.2a 37.8 ± 6.5a
14.7 ± 3.4 38.2 ± 7.11
14.8 ± 3.5 38.3 ± 7.6
92.7 ± 7.0
90.4 ± 7.4a,b
93.0 ± 7.3
94.0 ± 7.0
99.3 ± 4.4
97.8 ± 6.6a,b
100.6 ± 4.4
100.5 ± 5.1
0.93 ± 0.06 3.62 ± 0.29 3.16 ± 0.46 7.35 ± 0.78 5.28 ± 1.01 5.74 ± 0.85 2.06 ± 0.56 26.8 ± 5.5
0.93 ± 0.09 3.78 ± 0.46a,b 3.48 ± 0.59a,b 7.69 ± 0.94a,b 5.84 ± 1.20a,b 5.97 ± 1.12* 2.29 ± 0.66a,b 29.9 ± 6.8a,b
0.92 ± 0.06 3.58 ± 0.34 3.38 ± 0.66 7.28 ± 0.83 5.27 ± 0.93 5.68 ± 0.92 1.92 ± 0.46 25.3 ± 4.9
16-weeks
0.94 ± 0.07a 3.49 ± 0.40a 3.27 ± 0.63 7.04 ± 0.87a 5.20 ± 1.08 5.44 ± 0.79a 1.90 ± 0.44 24.6 ± 4.6
RMSSD, root mean square of successive differences. HF, high frequency spectral power. Ln, natural logarithm. VO2peak, peak oxygen uptake. a P b 0.05, significantly different than baseline value within group. b P b 0.05, significantly different from CON at the same time point.
maintained across the intervention period (Table 3). For the control group, no significant changes in body composition parameters were observed at the follow-up examination (P N 0.05), except for body weight (ES = 0.14, trivial, P b 0.05), BMI (ES = 0.19, trivial, P b 0.05) and waistto-hip ratio (ES = 0.30, small, P b 0.05). The exercising group had greater SDNN (ES = 0.42, small), RSSMD (ES = 0.68, moderate), TP (ES = 0.39, small), HF (ES = 0.50, small) and LF (ES = 0.23, small), after the intervention (P b 0.05). For CON group, significant decreases in SDNN (ES = 0.24, small), TP (ES = 0.28, small) and LF (ES = 0.33, small) were demonstrated across the intervention period, except for RSSMD and HF (P N 0.05, Table 3).In addition, compared with baseline, training increased relative VO2peak by 11.6% in IN (ES = 0.48, small, P b 0.05). Control subjects had no significant change in VO2peak from baseline to 16 weeks (P N 0.05). Table 4 depicts correlation coefficients (r) for changes between heart rate variability and body composition variables and aerobic fitness (n = 117). Subjects with greater individual changes in vagal-related HRV variables had more changes in body/trunk fat and a greater increase in absolute VO2peak over the intervention period (Fig. 1). The results of the stepwise regression procedures revealed that changes in trunk fat percentage, waist circumference and absolute VO2max accounted for the variance in RSSMD ln (R2 = 0.557, P b 0.05). For HF ln, the change in trunk fat mass and body weight accounted for the variance in HF ln (R2 = 0.417, P b 0.05). For TP ln, the BMI accounted for the variance in TP ln (R2 = 0.132, P b 0.05). No other variable added statistical significance (P N 0.05) to the regression models and therefore was removed from the models. 4. Discussion The main findings of the present study demonstrate that autonomic function improves with fat loss after an aerobic training program in overweight/obese adults. Changes in resting HRV were significantly related to later body composition changes. Moreover, the subjects with more vagalrelated HRV changes had greater enhancement of physical fitness.
Table 4 Correlation coefficients (r) of changes between heart rate variability and selected body composition variables and aerobic fitness after adjustment on age (n = 117).
△Body weight (kg) △Body fat mass (kg) △Body fat percentage (%) △Trunk fat mass (kg) △Trunk fat percentage (%) △Waist circumference (cm) △Waist-to-hip ratio △Body mass index (kg·m−2) △VO2 peak (l·min−1) △VO2 peak (ml·kg−1·min−1)
△SDNN ln ms
△RSSMD △TP ln ms ln ms2
△HF ln ms2
△LF ln ms2
−0.204a −0.143 −0.196a −0.152 −0.229a −0.051 −0.020 −0.186a
−0.420a −0.362a −0.406a −0.364a −0.436a −0.258a −0.167 −0.409a
−0.341a −0.172 −0.164 −0.178 −0.198a −0.201a −0.100 −0.361a
−0.369a −0.311a −0.300a −0.344a −0.348a −0.092 −0.086 −0.353a
−0.048 −0.131 −0.092 −0.030 −0.027 −0.061 −0.091 −0.032
0.083 0.240a
0.437a 0.424a
0.155 0.211a
0.296a 0.269a
0.125 0.194
△ = 16 week value-baseline value, VO2 peak peak oxygen uptake. a P b 0.05.
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Fig. 1. Association between individual training response (changes in selected body composition parameters and relative VO2peak) and cardiac vagal activity changes ● IN group, ○ CON group.
Overweight or obesity per se is associated with an increased risk of cardiovascular diseases, and previous studies suggest that cardiac autonomic control of heart rate is blunted due to excess fat and weight gain [23–25]. Our findings indicate that greater fat loss in individuals with more vagal-related HRV variable improvements, supporting previous findings in overweight/obese individuals, which reveal that depressed HRV could be reversed after dietary weight loss interventions, exercise training or combinations of both [10–12,26]. It is believed that impaired autonomic control of heart rate is associated with increased risk of cardiovascular mortality and that improvements in HRV variables are independent protectors against sudden death [2]. Moreover, consistent with previous multiple cross-sectional studies [27,28], our data demonstrate that central adiposity influences autonomic function. Indeed, we found that subjects with more central fat loss (measured by waist circumference and trunk fat percentage) had more improvement in HRV. In this context, perhaps, more favorable HRV profiles may be seen later with weight control as the proportion of fat loss increases.
Although the influence of weight status on HRV has been studied extensively [27,29], the link between weight loss and beneficial alterations in cardiac autonomic function is unclear. For example, in one study, data did not reveal significant changes in HRV variables after weight loss [30]. In another study, continuous endurance training with moderate intensity did not influence resting HRV in obese women in the absence of fat loss [31]. Of note, our subjects on a progressively increased (lowto-moderate) intensity training regimen experienced significant changes. Unlike previous findings [32], our current study clearly demonstrated significant correlations between changes in HRV and fat loss after aerobic exercise. Methodological differences in HRV recording and proxy measures of body composition may partly explain inconsistencies between our results and those of previous studies. Even so, our observations indicate that the effect of training on autonomic function might be influenced by body fat loss in addition to exercise duration and intensity. To our knowledge, however, the mechanisms by which fat loss favors increased autonomic function are still unclear. Alterations
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of several potential factors might be involved, such as insulin resistance [33], leptin [34] and inflammation [35]. How improvements in autonomic function occur after fat loss warrants future studies. Large inter-individual differences in vagal modulation changes with fat loss were observed in our subjects (Fig. 1) and these data extended and clarified an earlier study [26]. A previous cross-sectional HRV study revealed worse profiles for women with upper-body rather than lower-body obesity and with visceral rather that subcutaneous obesity [36]. Another study confirmed lower parasympathetic and greater sympathetic modulation of HRV in obese girls with higher central fat compared to those with lower central fat [27]. Thus, individual differences in HRV response might be attributed to regional fat distribution [24,28]. These observed changes in vagal-related HRV variables were significantly associated with changes in trunk fat percentage and/or waist circumference further support the aforementioned concept. Although autonomic function appears to be influenced in individuals with central adiposity in our current study, low R2 values revealed that reduced central fat does not fully explain variations in HRV. A prior study suggested that a hypocaloric diet associated with exercise training, in contrast to a hypocaloric diet alone, had more effects on autonomic activity [10]. In our laboratory, correlation procedures were significantly correlated between increased aerobic fitness (VO2peak) and changes in HRV variables. These results were further supported by the stepwise regression procedures, which revealed that changes in absolute VO2peak partially accounted for variation in RMSSD. Our data are consistent with the idea that training improves autonomic function [37,38]. Individual differences in the responsivity of aerobic fitness to exercise training might also be linked to variances in cardiovascular autonomic control and this idea agrees with increasing evidence to suggest that HRV may be useful for predicting individual aerobic fitness in response to training [38]. The subjects studied represented a relatively large BMI range which may offer a better understanding of the link between cardiac autonomic function and body composition. Trends in improved HRV that are associated with reduced obesity observed after aerobic training appear to reinforce the concept of a cardiovascular protection mechanism, and at the same time offered information regarding decreased mortality and morbidity from cardiovascular disease with appropriate lifestyle adaptations. Furthermore, our positive findings will contribute to the ongoing debate concerning non-invasive measurement of HRV for monitoring benefits of exercise interventions for overweight/obese individuals and suggest effective anti-obesity strategies. However, the study has several limitations. Firstly, although men and women were included in both groups, there were no sex-related differences in HRV at baseline or after exercise training. Also, the age range of the subjects was large, and the sample was biased which may affect statistical analysis. Additionally, the HRV was measured during spontaneous breathing at rest is a limitation of this study. Nevertheless, breathing frequency was in the high frequency range (0.15–0.50 Hz) and vagal-related HRV variables during spontaneous and paced breathing did not differ significantly [39]. The limit between high- and low-frequency fields of R–R interval variability in the power spectral analysis has been set [1] so that only breathing frequency of b 9 breaths·min− 1 gives a respiratory peak to the low-frequency field. Therefore, it is unlikely that our training protocol could have decreased the breathing frequency enough to influence the results, even if training is believed to decrease breathing frequency. Finally, this longitudinal study revealed decreased adiposity and increased VO2peak after the intervention. Therefore, the independent influences of body composition and aerobic fitness on autonomic activity are confounded. Future research should identify the distinct influences of both variables and the mechanisms that underlie the relationship between cardiovascular autonomic function and body composition.
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