The assessment of heart rate variability (HRV) has rapidly evolved from what was predominantly a research tool to an increasingly appreciated clinical modality (1). Its most widespread translational use at present is in the assessment of psychological stress, physical fitness, and the prevention of overtraining (1,27). The improved portability and reduced cost of HRV measurement equipment have also played a significant role in this regard. HRV assessment relies on the detailed assessment of the variations in the time intervals between consecutive heart beats, which are subject to continuous autonomic control (12,27). From these data, the changes in the beat-beat intervals over time (time domain analyses) can be more robustly quantified from as little as 1–5 min of recording (1,28,29). The beat-to-beat data can be further examined by using frequency domain analysis whereby the generated sinusoidal waveforms of these intervals over time are placed into various frequency components, allowing for a more in depth analysis of autonomic balance (12,27).
An area of recent interest has been in the effects of high altitude (HA) on HRV (4,7,8,21). HA exposure challenges several physiological systems that are heavily reliant on continuous autonomic control and are likely to influence HRV (7,8,22,23). Acute hypoxia and HA lead to marked sympathetic activation, yet paradoxically, there is also evidence of increased competing parasympathetic activity, which contributes to the reduction in maximal heart rate in proportion to the altitude gained (7,8,20,22). Hypobaric hypoxia, cold, exercise, stress, and fatigue, which are synonymous with HA exposure, are all known individually to influence HRV (8,17).
There are data to suggest that acute hypoxia and HA exposure lead to a decline in HRV (8,21), with conflicting data on its potential link to HA-related symptoms and acute mountain sickness (AMS) (13,14,29). Published studies on HRV at HA have been derived from relatively small cohorts, with very few data on the effects of genuine terrestrial, rather than simulated HA (5,13,14). Moreover, there has been an underrepresentation of women, in current data sets, despite their obvious physical and potentially important physiological differences compared with men. Resting heart rate tends to be higher in women than in men, yet their stroke volumes and cardiac outputs are lower and these differences are sustained and even enhanced with hypoxia (6,15). Resting minute ventilation, which affects HRV, is relatively greater in women under both normoxia and hypoxia (24). Time domain measures of HRV are typically higher in healthy men (<50 yr) compared with age-matched women (6,15,25). However, the power spectral density (PSD) of HRV in women is usually characterized by less total power (TP), greater or similar high-frequency (HF) and lower low-frequency (LF) power, and LF:HF ratios (12,15,28).
There are some data suggesting that women may be also more vulnerable to both AMS development and worsening symptom severity compared with men (9,19,26). Given the possible sexual dimorphism in HRV and AMS incidence/severity coupled with the reported links between HRV and AMS, an investigation of comparative HRV in men and women and its relationship to AMS development is warranted.
In this study, we aimed to investigate, for the first time, the influence of sex on time and frequency domain measures of HRV with increasing terrestrial HA and its potential link to AMS development.
METHODS
Study design and participants
Sixty-three healthy British Military servicemen older than 18 yr were included. They were all assessed at near sea level (SL; <200 m) and again at three further altitudes during progressive HA ascent in the Dhaulagiri region of the Himalayas in March/April 2016. Health status was confirmed after a detailed baseline questionnaire. For inclusion, all subjects needed to be low-altitude dwellers and were required to be deemed medically fit for HA exposure by their medical practitioners. All participants were required to have successfully completed their mandatory military personal fitness assessment 1.5-mile run in accordance with published standards (adjusted to age and sex) before inclusion. This run was undertaken in sports clothing on a flat surface. Subjects with a history of cardiac arrhythmias were excluded. The subjects were studied consecutively in groups of 8–14 at SL and at HA with a 2-d stagger between successive groups. All trekking groups followed an identical ascent and exercise recovery profile with similar morning wake times. SL baseline assessments were performed in the United Kingdom approximately 6 wk before each departure.
HA ascent and descent profile
The subjects flew from the United Kingdom to Kathmandu (1400 m), where they underwent 2 d of local acclimatization (days 1–3). Thereafter, they traveled by road for 2 d to 1030 m (Darbang). From there, they commenced trekking on foot over the ensuing 11 d to an altitude of 5140 m (with an overpass of 5360 m) before commencing their decent on foot to Marpha (2719 m) and then by road back to Kathmandu. Research assessments were performed at SL and at static research camps at 3619, 4600, and 5140 m during HA ascent.
Physiological assessments and HRV
Oxygen saturations (SpO2) were measured using a Nonin Onyx (Nonin Medical Inc., Plymouth, MN) pulse oximeter with sampling for approximately 15 s. HA-related symptoms were recorded using the Lake Louise Scoring (LLS) system. AMS was defined as an LLS of ≥3 in the presence of headache (11,16). HRV assessments were undertaken using dedicated battery-operated portable HRV devices that record a single-lead ECG at a sampling rate of 250 per second (CheckMyHeart Plus™; Daily Care Biomedical, Taoyuan, Taiwan) as previously described (6). The first of the two surface ECG electrodes were placed at the right sternal edge at one finger breathe below the suprasternal notch and the second over the left fifth intercostal space at the midclavicular line (i.e., cardiac apex). Measurements were taken on fully rested subjects during a 5-min period in the early morning after micturition and before breakfast or caffeine (4). All subjects were studied seated in a warm building at SL and wearing warm clothing and in a tent at HA and were advised not to talk during HRV assessment. All stored recordings were exported via USB hook up for offline data analysis (CheckMyHeart Plus™ R30 V4; Daily Care Biomedical).
The R waves of the stored ECG were used as the fucidal point to determine the beat-to-beat interval with full ECG disclosure. Non–normal-to-normal (NN) intervals and ectopic beats were identified using customized software nonlinear algorithms and were highlighted by color coding within the HRV software to ease their identification. All ECG data were inspected in 6-s windows for further identification and manual editing of potential non-NN intervals if necessary. All confirmed non-NN intervals due to ectopy were excluded. The average 5-min heart rate and the SDNN, RMSSD, NN50, and pNN50 time domain measures, as previously described, were recorded (12,27). The SDNN refers to the SD of the NN intervals from the acquired ECG. The root mean square of successive differences (RMSSD) is the square root of the mean of the squares of the successive differences between adjacent NN intervals. The NN50 describes the number of pairs of successive NN that differ by >50 ms, and the pNN50 refers to the proportion of NN50 divided by total number of NN intervals. Frequency domain analysis was performed using the non-detrend method of fast Fourier transformation with full graphical display of the power spectral data. Key frequency band data collected were the HF power (0.15–0.40 Hz), LF power (0.04–0.15 Hz), very low-frequency (VLF) power (0.01–0.04 Hz), TP, and the LF:HF ratio as previously defined (22,24). Normalized HRV values of LF (LFnu) and HF (HFnu) were calculated as a percentage of the total spectral power minus the VLF, respectively (12).
Ethics
All participation was voluntary, and all subjects underwent detailed written informed consent. This study was approved by the Ministry of Defence Research and Medical Ethics Committee and was conducted according to the standards of the Declaration of Helsinki.
Statistical analysis
Data were analyzed using GraphPad InStat version 3.05 and SPSS® statistics version 22, with all graphical figures presented using GraphPad Prism version 4.00 for Windows (GraphPad Software, San Diego, CA). Sample size calculations were performed using a proprietary-determined sample size calculator using GraphPad StatMate version 2.00 for Windows. Data inspection and the Kolmogorov–Smirnov test were undertaken to assess normality of all continuous data, which were presented as mean ± SD and as the SEM for figures. Categorical variables were compared using a chi-squared test. Comparison of unpaired data was performed using an independent t-test and a Mann–Whitney test for parametric and nonparametric data, respectively. Correlations were performed using Pearson and Spearman rank correlation (±95% confidence interval (CI)) for parametric and nonparametric data, respectively. A factorial repeated-measures ANOVA with Bonferroni correction (to minimize Type I error) was performed to assess the main effect of sex (men vs women) over the four altitude time points (SL, 3619 m, 4600 m, and 5140 m) and any interaction of altitude–sex on HRV scores. Binary logistic regression analyses (enter) were undertaken to assess potential continuous HRV and other univariate predictors of AMS development (yes or no) and its coefficient (B). We also undertook an additional exploratory analysis of the categorical HRV measures of RMSSD of <30 ms, LF:HF of >1.3, and LFnu of <20% that have been previously reported to be associated with AMS (13,14). Nonparametric data were log (Ln) transformed, and normality confirmed for the ANOVA and logistic regression analyses. A two-tailed P value of <0.05 was considered statistically significant for all comparisons.
Sample size calculations
In a recent pilot study in Dhaulagiri, which included 12 subjects, we observed a nonsignificant but 11% (−7.9 ms) fall in the RMSSD time domain measure of HRV from baseline to 3600 m using identical HRV (CheckMyHeart Plus™) devices (4). Hence, by studying an even greater altitude of >5000 m, we calculated that a sample size of >18 subjects in each group (men vs women) would have a >80% power to detect a significant change in the RMSSD at HA at a significance level (alpha) of 0.05 (two-tailed). In another recent study, Saleem et al. (25) documented that the SDNN was significantly higher in 27 healthy men than in 18 healthy women. We estimated that a sample size of at least 18 women and >30 men studied across four differing altitudes would have sufficient power to detect a significant sex difference in HRV including SDNN.
RESULTS
HRV data were available on 62 subjects at SL and at 3619 m and on 58 subjects at 4600 and 5140 m, respectively. The men (31.2 ± 9.3 yr) and women (31.7 ± 7.5 yr) were well matched for age, ethnicity, smoking history, and body mass index (Table 1). As expected, the men were on average taller and heavier with higher systolic blood pressures at baseline, with faster completion times for their mandatory annual 1.5-mile running fitness test (P < 0.0001; Table 1).
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TABLE 1: Baseline demographics.
HA exposure led to a significant fall in SpO2 and an increase in LLS among both men and women compared with baseline with no effect for subject sex (Table 2). Heart rate (5-min average) increased at HA in both sexes, with women having consistently higher rates than men both at SL and at HA (Tables 2 and 4).
TABLE 2: Changes in SpO2 and time domain measures of HRV at SL to increasing HA.
There was a significant main effect for altitude on all time domain measures of HRV. On post hoc analysis, this represented a significant reduction in time domain measures of HRV most consistently between 3619 and 5140 m (Tables 2 and 4; Fig. 1). There was a significant main effect for altitude on LF power, HF power, and TP. This difference was again most marked on post hoc analyses between 3619 and 5140 m, where significant reductions in LF power, HF power, and TP were observed (Tables 3 and 4; Fig. 2).
TABLE 3: Changes frequency domain measures of HRV at SL to increasing HA.
TABLE 4: Results of two-way repeated-measures ANOVA comparing the main effects of altitude (SL, 3619 m, 4600 m, and 5140 m) and sex (men vs women) on measures of HRV.
FIGURE 1: Comparative changes in the RMSSD (mean ± SEM) among men and women at SL and increasing HA. Posttest differences on repeated-measures ANOVA: *vs SL, †3619 vs 4600 m, ‡3619 vs 5140 m.
FIGURE 2: Comparative changes in LF (LnLF) power (mean ± SEM) among men and women at SL and increasing HA. Posttest differences on repeated-measures ANOVA: *vs SL, ‡3619 vs 5140 m.
Time domain measures of HRV were nonsignificantly higher in men at SL and significant differences emerged at HA, where all measures were notably higher in men (Tables 2 and 4; Fig. 1). There was also a main effect for sex among the frequency domain measures of TP, LF power, and HF power, which were all significantly higher in men at HA (Tables 3 and 4, Fig. 2). There were no interactions between sex (men vs women) and altitude (SL, 3619 m, 4600 m, and 5140 m) on any measures of HRV (Table 4) or heart rate.
SpO2 inversely correlated with LLS (r = −0.38; 95% CI, −0.50 to −0.24; P < 0.0001) and positively with RMSSD (r = 0.16; P = 0.02), SDNN (r = 0.18; 0.05–0.30, P = 0.007), VLF power (r = 0.17; 0.04–0.30; P = 0.01), LF power (r = 0.16; 0.03–0.29; P = 0.2), and TP (r = 0.17; 0.03–0.29; P = 0.02).
The prevalence of AMS increased at HA from 15.2% at 3619 m to 27.3% at 4600 m and 32.5% at 5140 m (P = 0.004). Reducing SpO2 (B = −0.13; P < 0.0001) and increasing altitude (B = 0.80; P < 0.0001) and mean heart rate (B = 0.03; P = 0.04) were the only univariate predictors of AMS. None of the continuous measured HRV parameters or the categorical variable of subject sex (men vs women) were predictive of AMS. RMSSD of <30 ms, LF:HF of >1.3, and LFnu of <20% were not predictive of or associated with AMS.
DISCUSSION
This is the largest study to assess the effects of HA on HRV and, to the author’s knowledge, the first study to investigate the influence of sex on HRV at terrestrial HA. In this study, HRV was influenced by HA. Minor sex-related differences in HRV that were observed at SL were sustained at genuine terrestrial HA. A link between HRV and symptoms of AMS was not found.
We observed a significant fall in resting SpO2 and an increase in LLS with increasing HA. There was also a significant main effect for altitude on heart rate (which increased) and all the evaluated time domain measures of HRV. The most consistent change was between 3619 and 5140 m and hence at higher altitude, where there was a significant fall in SDNN, RMSSD, NN50, PNN50, LF, and HF power. These findings are in keeping with published data that have shown a fall in time domain measures of HRV at HA (13,14,29). These changes are in part explained by a number of factors linked to the HA environment. These include reducing sleep quality, extremes of cold and heat, physical exhaustion, and increasing anxiety, which are all known to adversely affect and reduce the time domain measures of HRV (14,20,30).
We also observed a significant main effect for sex on heart rate and time domain measures of HRV at HA, with men having consistently higher scores and greater variability. This is a novel finding. Although published data have shown a consistent trend to higher time domain measures of HRV in young adult men than in women at SL (3,15,25), this is the first comparative study at HA. The trend to higher time domain HRV measures at SL became significant at HA. There was no interaction of altitude on sex on the time domain HRV parameters. This finding can be partly explained by the sex differences in heart rate, which was consistently lower in the men. Heart rate is well known to inversely correlate with all main time domain measures of HRV (12).
We also observed a significant effect of altitude (SL, 3619 m, 4600 m, and 5140 m) on TP, VLF power, LF power, and HF power. The most consistent finding on post hoc analyses was a reduction in these parameters at the highest altitude of 5140 m versus SL and 3619 m. HA exposure was also associated with a significant main effect of sex with greater TP, LF power, and HF power among the men. Results from a very recently published meta-analysis of comparative HRV measures among men and women at SL that included more than 60,000 participants demonstrated that when compared with that seen in women, PSD in men is generally characterized by lower HF power and greater LF power, TP, and LF:HF ratios (15). This is thought to reflect their higher resting sympathovagal tone (hence greater LF power and LF:HF ratios) compared with women. Our LF data support these previous data. However, contrary to the published data, we found that HF power was actually higher with variable effects on LF:HF power among the men. There are several potential factors that might explain these results. It is known that LF power, HF power, and their relative ratios (LF:HF) can be markedly influenced by a number of factors, which include age, respiratory rate, recording length, and heart rate (3,12,15,24,27). Although the ages were similar between the men and the women, the greater heart rates in women would have led to the analysis of a higher number of beat-to-beat intervals, despite an identical recording period, which could be an important confounder. Second, although increasing heart rate and minute ventilation at HA are thought to relate to enhanced sympathetic activation, there is also evidence of elevated parasympathetic neural activity (5,7,22,23). This increase in competing vagal activation at HA is thought to contribute to the reduction in maximal heart rate at HA (7). LF power and the LF:HF ratio have been traditionally thought to represent sympathetic activation and net sympathovagal balance, respectively, with RMSSD and HF power reflecting parasympathetic nerve activity (12). However, there is evolving evidence to show that these arbitrary assumptions about the discrete autonomic effects these HRV measures may be overly simplistic (2).
Our identified sex-related dissimilarities in the time and frequency domain HRV measures at HA could also relate to differences in fitness levels. Indeed, the men in our study had higher time domain measures of HRV and lower 1.5-mile run times. Our findings could also relate dissimilarities in acclimatization in men versus women. Acclimatization encompasses the cumulative effects of multiple factors such as hydration, ventilation, and enuresis that are known to influence autonomic balance and HRV (10). HRV and in particular frequency domain analysis can be significantly affected by breathing pattern and ventilation, which are markedly affected by HA where hypoxia-driven hyperventilation predominates (15,18,19). In our study, paced breathing during HRV assessments was not performed, but the participants were encouraged to relax and breathe normally. Most published studies on HRV at HA have used spontaneous nonpaced breathing and hence were keen to use a comparative methodology (7,9,10,25). Our participants were assessed at far higher altitudes and under greater hypoxia than most of the previous HA HRV studies to date; hence, the potential challenge to paced breathing was likely to have been greater. We anticipated that at 4600 and 5140 m, controlled breathing under significant hypoxia and a high ventilatory drive might paradoxically increase subject anxiety and perceived breathlessness. By enforcing a similar paced breathing protocol in both men and women, we risked neutralizing genuine sex-related differences in HRV related to well-reported dissimilarities in ventilation between men and women at HA (2,20). Unfortunately, we did not measure comparative respiratory rate and ventilation among the men versus women. This is an obvious limitation because sex-related differences in their spontaneous breathing could have provided further insight into the observed differences in HRV identified.
We did not observe a link between AMS and HRV in this current study. There is limited evidence linking changes in HRV to AMS, raising the prospect of using HRV as a noninvasive predictor of AMS development (9,10). In a previous study, Karinen et al. (14) investigated 36 different healthy climbers ascending from 2400- to 6300-m altitudes during five differing expeditions and noted that a lower RMSSD and HF at 2400 m was a marker of AMS at 3000 to 4300 m. However, contrary to our study, the speed of ascent varied between their five studied groups. Furthermore, they measured HRV for 2 min rather than 5 min. In another study, of similar size (n = 32), Huang et al. (13) noted that an HF% of <20% (nu) or an LF:HF ratio of >1.3 at lower altitudes was predictive of AMS at 3400 m. These HRV parameters failed to be either associated or predict AMS in or study. Wille et al. (17,24,29) in a prolonged normobaric hypoxia study and our group in another recent study (ithlete RMSSD-derived HRV score) failed to identify a clear link between AMS and HRV supporting our data.
The potential reasons for the contradictory findings in HRV to predict AMS may relate to differences in study design, HA environment, ascent/hypoxic profile, HRV recording time, and the actual HRV parameters measures. Even the definitions of AMS that were used differed between these studies. For example, Karinen et al. defined AMS as an LLS of ≥3 in their study, whereas in the study by Wille et al., an LLS of ≥4 was used to define AMS (10,25,29). In our study, we used the Lake Louise consensus definition (1992) for AMS, which refers to an LLS score of ≥3 in the presence of headache (5,8,13). It is well known that AMS is a highly complex and heterogeneous condition. Its causative mechanisms include changes in cerebral arterial blood flow and increased vascular permeability within the blood–brain barrier, both of which may be influenced by local autonomic control (19). Although HRV reflects overall cardiac autonomic control, it is relatively nonspecific and is not indicative of local autonomic balance (2,19).
This study has several additional imitations that should be mentioned. The subjects were studied in consecutive groups of 8–14 two days apart and not all together in one batch. This was because of the large sample size for this type of remote field study and the need to undertake at HRV in the early morning before breakfast and caffeine. We measured 5-min HRV, which may be more vulnerable to short-term sex and situational bias than that obtained from longer recordings (23). However, 5-min HRV measurement is well validated and endorsed by the current HRV Task Force guidelines and is more potentially applicable to clinical practice than that of longer recordings (23). We included a larger proportion of men than women and cannot exclude the possibility of sample bias, despite their similarities in age, ethnicity, smoking history, and body mass index.
In conclusion, our findings indicate that increasing HA was associated with a reduction in HRV, which was most notable at 4600 m and greater. There were significant sex-related differences in HRV between men and women, which were sustained at HA. There was no interaction between sex and altitude on any of the HRV parameters measured. These sex-related differences may reflect dissimilarities in their autonomic balance and acclimatization to HA. HRV was not predictive of AMS.
The authors would like to thank the Surgeon General. We also like to sincerely thank the subjects for their time and for volunteering to take part in this study.
This projected was funded by a variety of sources, and the main funders include the Royal Centre for Defence Medicine, a grant from the Royal Navy Royal Marines Charity, and the Poole Hospital Cardiac Research Fund.
C. J. B. has received speaker’s fee and consultation fees from Pfizer, Bristol Myers Squibb, Astra Zeneca, and Boehringer-Ingelheim. A. M. has received speaker fees from Medtronic. The other authors report no conflicts. Results of this study do not constitute endorsement by the American College of Sports Medicine.
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