3.1. Baseline Clinical Characteristics
There were no differences in age and gender between the investigation and control groups (Table 1
). In subjects with MetS, components were distributed as follows: Increased arterial blood pressure and increased waist circumference was present in all 69 subjects (100%); low high-density lipoprotein cholesterol levels were found in 55 (80%), elevated fasting triglyceride levels in 44 (63.8%), and impaired fasting glucose in 38 (55.1%) subjects; diabetes was present in 10 (14.5%) of MetS subjects. A significant difference between MetS and control groups was observed with respect to all risk factors.
Clinical assessment showed that blood pressure stage I and II were uniformly distributed in subjects with MetS (46.6% and 53.6% respectively). The mean 24 h, diurnal/nocturnal systolic and diastolic blood pressure was significantly higher in the MetS group (p < 0.001). More than two thirds (47, 68.1%) of MetS group subjects were on antihypertensive medication—17 (24.6%) were on beta-blockers, 35 (50.7%) on ACE inhibitors, 10 (14.5%) on angiotensin receptor blockers, 17 (24.6%) on calcium channel blockers, 16 (23.2%) on diuretics, and 38 (55.1%) used other drugs.
3.2. Heart Rate Variability Characteristics Before the Elimination of Physical Activity Influence
Heart rate variability data are presented in Table 2
. There was no significant difference in SDNN between the study group and controls. However, the analysis of the 5-min RRI segments revealed that the SDNN index is reliably lower in the MetS group (47.8 ± 13.0 ms vs 53.8 ± 14.1 ms, p
< 0.05), whereas SDANN did not differ significantly. The analysis of even shorter RRI segments calculating the variability of adjacent RRI values (RMSSD and pNN50) showed that these indices were lower in the MetS group. This trend is observed in the MetS group after applying the Poincaré distribution. The short-term beat-to-beat RRI variability from the Poincaré plot (width) SD1 was 14.2 ± 5.4 ms in the control group and 12.9 ± 4.9 ms in the MetS group (p
> 0.05). The long-term beat-to-beat RRI variability from the Poincaré plot (length) SD2 was respectively 151.6 ± 37.5 ms vs 147.9 ± 37.0 ms (p
> 0.05). These time-domain data indicate that subjects with MetS exhibit a tendency to decrease in HRV.
The frequency-domain analysis showed that the RRI variability in the VLF bandwidth did not differ between the groups. Significant difference was evident in the LF bandwidth: 5.86 ± 0.61 ln ms2 in control group vs 5.51 ± 0.59 ln ms2 in MetS (p < 0.01). In the HF bandwidth, only a downward trend was observed in the MetS group. Consequently, the LF/HF ratio was reliably lower in the MetS group (3.62 ± 1.35 vs 3.04 ± 1.37, p < 0.05), indicating that subjects with MetS exhibit a decrease in day-time variability of HR.
During the night-time period, when subjects were in the nonmotile state, slow HR was present in both groups, and all RRI time-domain variables reliably differed from the day-time measures. The night-time SDNN decreased to 93.0 ± 31.1 ms (p < 0.05) in the control group, and to 90.0 ± 26.4 ms (p < 0.05) in the MetS group, whilst the SDNN index in the control group did not change, and in the MetS group, increased to 54.3 ± 16.7 ms (p < 0.05). Furthermore, in the control and study groups, SDANN sharply decreased to63.2 ± 20.0 ms and 64.4 ± 20.9 ms (p < 0.001), respectively, indicating that the effect of the sympathetic nervous system on heart rate fluctuation decreased during the night.
The difference between adjacent RRI was very high (p < 0.001): during the night-time, RMSSD increased to 27.9 ± 10.7 ms and 27.8 ± 11.8 ms, and pNN50 to 8.9 ± 8.6% and 9.4 ± 9.5%. Furthermore, Poincaré plot indicators changed similarly. This dynamic allows us to state that parasympathetic HR regulation was equally highly expressed in both groups overnight.
The frequency-domain analysis of the night-time RRI segments showed different results. Firstly, the variability of RRI at night, as compared to the day-time measures, increased only in the high-frequency band: in the control group, from 4.66 ± 0.77 ln ms2 to 5.24 ± 0.87 ln ms2 (p < 0.01), whereas in the MetS group, from 4.50 ± 0.81 ln ms2 to 5.13 ± 0.92 ln ms2 (p < 0.01). Secondly, among subjects with MetS the VLF variable decreased to 7.52 ± 0.58 ln ms2 (p < 0.05). Thirdly, in contrast to the control group, the magnitude of LF in the MetS group has decreased statistically significantly. Likewise, the decrease of nocturnal LF/HF ratio was more pronounced in the MetS group (1.95 ± 1.16 (p < 0.001) vs 2.15 ± 1.03 (p < 0.001)). To summarize, the relationship between SNS and PNS effects on night-time HR varied, and day-time LF/HF differences between the groups disappeared during the night.
We have noticed that there were many individuals whose daily pulse rate was higher, which is known to reduce HRV. The diurnal HR distribution analysis showed that the average pulse rate of all subjects during the day was higher than 60 bpm and reached up to 120 bpm (Figure 5
The latter result necessitated an additional analysis, which showed that HRV and pulse rate were highly interdependent: more frequent HR was associated with lower HRV. The correlation coefficient between the averaged RRI and HRV time-domain components varied from r = 0.39 to r = 0.53. This relationship indicates that the higher the SNS tone level (lower RRI), the lower the HRV (Figure 6
). In addition, all HRV indices were reliably lower among subjects with increased HR than in the group with a less frequent HR (p
A subsequent GLM Multivariate analysis confirmed that the HRV daily indices (RMSSD, SDSD, and SD1) and SDNN index were reliably (p < 0.003) lower in the MetS group than in control subjects.
The heart rate histogram demonstrates that the shift of all heart rate averages from 60 bpm to tachycardia is associated with the dominance of the day-time sympathetic nervous system and a subsequent decrease of HRV variables: SD1, SDSD, RMSSD, and SDNN index (Figure 6
3.3. Heart Rate Variability Characteristics after Elimination of Physical Activity Influence
During the 24 h Holter monitoring in the outpatient setting, subjects are constantly exposed to physical activity. Hence, this raises the question of whether it is possible to eliminate the influence of this physical activity which is recorded by an actigraph, and to bring the HRV assessment closer to the measurements obtained under stationary conditions in a laboratory. Therefore, in the next step, we analyzed the daily HRV after the elimination of the influence of physical activity. Our analysis included a comparison of the individuals with and without metabolic syndrome, and of the day- and night-time HRV data.
Our results have shown that an actigraph can be used to ascertain the change in HR associated with physical activity. First of all, this association is confirmed by the relatively high negative correlation between RRI and physical activity (r = −0.44 ± 0.13), which has decreased after eliminating the influence of PhA (r= −0.12 ± 0.2). Since PhA occurs during the day-time period, only day-time HRV indicators were analyzed. HRV data after PhA influence elimination is presented in Table 3
and Figure 7
. A statistically significant change (presented as delta mean) was observed with respect to each variable (p
We observed that, after PhA influence elimination, the mean RRI changed by −62.3 ms (p
< 0.001) in the control group, and by −75.6 ms in the MetS group (p
< 0.001, see Table 2
and Table 3
). Hence the elimination of PhA influence reduced the overall effect of SNS on heart rate. In both groups, long-term indices (SDNN, SDANN, and SD2) did not change. By contrast, RRI segments of adjacent RRI values (RMSSD, pNN50, and SD1) and 5-min RRI segments (SDNN) have significantly increased in both groups (p
< 0.001). An increase in the latter indices highlighted the HRV difference between the MetS and control groups: a significant (p
< 0.001) decrease of all short-term HRV variables was found in the MetS group (p
After the elimination of PhA influence, the frequency-domain analysis did not reveal any significant change in the VLF bandwidth, whereas in the LF bandwidth variability decreased, even if the difference between the groups remained significant (p < 0.01). HF bandwidth variability was not applicable for analysis since respiratory movements are inevitably recorded by accelerometers and fall within the same frequency bandwidth, thus producing PhA unrelated artifacts.
In sum, the elimination of physical activity-related SNS influence on HRV uncovers more pronounced short-term parasympathetic fluctuations in controls, but not MetS subjects. Our results, firstly indicate the real magnitude of the blunted HRV in the middle-aged MetS subjects with hypertension. Secondly, we demonstrated that the blunted HRV in these subjects is accounted for by the mitigation of parasympathetic tone.