• View in gallery

    A—Mean ± SEM HR as a function of time of day in 5 Thoroughbreds during 24 hours of rest in a stall (open circles) or 21 hours of road transportation (closed circles). B—High-frequency power (0.07 to 0.6 Hz) from Fourier analysis of HR power spectra as a function of time of day. C—Low-frequency power (0.01 to 0.07 Hz) from Fourier analysis of HR power spectra as a function of time of day. D—Low frequency-to-high frequency ratio as a function of time of day. Notice the results of nonlinear (stall rest) and linear (road transportation) regression analysis (solid lines), linear regression analysis fitted to stall rest data (dotted line), and linear regression analysis fitted to all but first transportation datum (a possible outlier; dashed line). Periods are indicated (horizontal bars) during transportation when the vehicle was stopped and horses were rested and given water (R), food (F), or both or were at sea on an automobile ferry.

  • View in gallery

    Top—High-frequency power as a function of LF-to-HF ratio in 5 Thoroughbreds during stall rest (open circles) or during road transportation (solid circles). Bottom—Low-frequency power as a function of LF-to-HF ratio. Notice linear regression results for road transportation (solid lines) and nonsignificant regression analysis results for stall rest (dotted lines). Data are plotted with LF-to-HF ratio as the independent variable to facilitate comparing HF and LF power correlations.

  • View in gallery

    Low-frequency power as a function of HF power in 5 Thoroughbreds during stall rest (open circles) or during road transportation (solid circles). Notice linear regression analysis results for stall rest and road transportation data (solid lines).

  • View in gallery

    Top—High-frequency power as a function of HR in 5 Thoroughbreds during stall rest (open circles) or during road transportation (solid circles). Middle—Low-frequency power as a function of HR. Bottom—Low frequency-to-high frequency ratio as a function of HR. Notice the linear regression analysis results for road transportation (solid lines) and nonsignificant regression analysis results for stall rest (dotted lines). Data are plotted with HR as the independent variable to facilitate comparison between HRV indices.

  • View in gallery

    Heart rate as a function of HF power and LF-to-HF ratio during road transportation as determined by backward stepwise linear regression analysis. Response surface is shown as a grid overlaying data points with drop lines.

  • View in gallery

    Heart rate as a function of LF power and LF-to-HF ratio during stall rest as determined by backward stepwise linear regression analysis. Response surface is shown as a grid overlaying data points with drop lines.

  • View in gallery

    Interrelationship between HR, HF power, and LF power during stall rest (open circles) and road transportation (solid circles). Separate response surfaces for stall rest and road transportation do not intersect despite significant overlap of HRs.

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Changes in heart rate and heart rate variability in Thoroughbreds during prolonged road transportation

Hajime Ohmura DVM, PhD1, Atsushi Hiraga DVM, PhD2, Hiroko Aida DVM, PhD3, Masayoshi Kuwahara PhD4, Hirokazu Tsubone DVM, PhD5, and James H. Jones PhD, DVM6
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  • 1 Equine Science Division, Hidaka Training and Research Center, Japan Racing Association, 535-13 Aza-Nishicha, Urakawacho, Urakawagun, Hokkaido 057-0171, Japan.
  • | 2 Equine Science Division, Hidaka Training and Research Center, Japan Racing Association, 535-13 Aza-Nishicha, Urakawacho, Urakawagun, Hokkaido 057-0171, Japan.
  • | 3 Equine Science Division, Hidaka Training and Research Center, Japan Racing Association, 535-13 Aza-Nishicha, Urakawacho, Urakawagun, Hokkaido 057-0171, Japan.
  • | 4 Department of Comparative Pathophysiology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyoku, Tokyo 113-8657, Japan.
  • | 5 Department of Comparative Pathophysiology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyoku, Tokyo 113-8657, Japan.
  • | 6 Department of Surgical and Radiological Sciences, School of Veterinary Medicine, University of California, Davis, CA 95616.

Abstract

Objective—To determine whether evaluation of heart rate (HR) and HR variability (HRV) during prolonged road transportation in horses provides a sensitive index of autonomic stimulation.

Animals—Five 2-year-old Thoroughbreds.

Procedure—ECGs were recorded as horses were transported for 21 hours in a 9-horse van. Heart rate, high-frequency (HF) power, low-frequency (LF) power, and LF-to-HF ratio from Fourier spectral analyses of ECGs were calculated and compared with values recorded during a 24-hour period of stall rest preceding transportation.

Results—HR, HF power, and LF power had diurnal rhythms during stall rest but not during road transportation. Heart rate was higher and HF power and LF power lower during road transportation than stall rest, and HR, HF power, LF power, and LF-to-HF ratio all decreased with time during road transportation. Heart rate during stall rest was weakly and inversely associated with LF power, but during road transportation was strongly associated with LF power, HF power, and LF-to-HF ratio. Neither LF power nor HF power was correlated with LF-to-HF ratio during stall rest, but LF power was strongly and HF power weakly correlated with LF-to-HF ratio during road transportation. High-frequency power and LF power were significantly correlated with each other during stall rest and road transportation. Heart rate was significantly influenced by LF power and LF-to-HF ratio during stall rest (R2 = 0.40) and by HF power and LF-to-HF ratio during road transportation (R2 = 0.86).

Conclusions and Clinical Relevance—HR is influenced by different sympathovagal mechanisms during stall rest, compared with during road transportation; HRV may be a sensitive indicator of stress in transported horses.

Abstract

Objective—To determine whether evaluation of heart rate (HR) and HR variability (HRV) during prolonged road transportation in horses provides a sensitive index of autonomic stimulation.

Animals—Five 2-year-old Thoroughbreds.

Procedure—ECGs were recorded as horses were transported for 21 hours in a 9-horse van. Heart rate, high-frequency (HF) power, low-frequency (LF) power, and LF-to-HF ratio from Fourier spectral analyses of ECGs were calculated and compared with values recorded during a 24-hour period of stall rest preceding transportation.

Results—HR, HF power, and LF power had diurnal rhythms during stall rest but not during road transportation. Heart rate was higher and HF power and LF power lower during road transportation than stall rest, and HR, HF power, LF power, and LF-to-HF ratio all decreased with time during road transportation. Heart rate during stall rest was weakly and inversely associated with LF power, but during road transportation was strongly associated with LF power, HF power, and LF-to-HF ratio. Neither LF power nor HF power was correlated with LF-to-HF ratio during stall rest, but LF power was strongly and HF power weakly correlated with LF-to-HF ratio during road transportation. High-frequency power and LF power were significantly correlated with each other during stall rest and road transportation. Heart rate was significantly influenced by LF power and LF-to-HF ratio during stall rest (R2 = 0.40) and by HF power and LF-to-HF ratio during road transportation (R2 = 0.86).

Conclusions and Clinical Relevance—HR is influenced by different sympathovagal mechanisms during stall rest, compared with during road transportation; HRV may be a sensitive indicator of stress in transported horses.

Variability in HR has been suggested to be a noninvasive index of autonomic nervous activity.1–3 Results of studies that use autonomic blockade and Fourier analysis of HR power spectra have indicated that the power spectrum of HRV in the HF power domain reflects primarily parasympathetic nervous tone. The sympathetic and the parasympathetic nervous systems have been shown to contribute to the LF power spectrum.1,2 Therefore, the LF-to-HF ratio has been suggested to be an index of cardiac sympathovagal balance.2,4 How these indices of HRV interact to influence or determine HR in animals subjected to environmental stimuli that elicit varying degrees of autonomic tone is poorly understood.

Horses are often transported to participate in racing, equestrian competitions, breeding, sales, or trail riding. It is well documented that transporting horses can produce a variety of physiologic responses, such as decreased body mass, increased heart and respiratory rates, increased concentrations of plasma cortisol and ACTH, and other variables indicating a stress response.5–16 The proximate cause of these responses is that horses are exposed to a variety of stressors during transportation, such as prolonged restraint, vibration, noise, and a potentially uncomfortable environment in the transportation vehicle.16 The occurrence of respiratory disease associated with transportation is sufficiently common that horsemen and veterinarians colloquially call it shipping fever. Immune depression associated with a stress response is widely regarded as being a contributing factor to its pathogenesis.16 It seems likely that a major component of this stress response is alteration of autonomic nervous function, as originally proposed by Selye17; however, the autonomic nervous response of horses to being transported is poorly understood.

Results of studies18 of HRV in other species of mammals (mostly humans) have shown that HRV indices decrease with stress. Sensitive detection of changes in a horse’s response to stressors would be valuable in evaluating experimental modifications of potentially stressful environments (eg, during transport).

We have reported on the use of power spectral analysis of HRV to assess autonomic nervous function in Thoroughbreds.19 We anticipated that application of this technique might provide a more sensitive indicator of the effects of transportation on autonomic nervous function in horses than the more commonly used index of HR alone, or other highly variable indices (eg, plasma cortisol concentration). We also expected such analysis to yield insights into the manner in which HRV indices interact to modify HR during a period of prolonged stress.

We expected that autonomic nervous system responses in Thoroughbreds being transported would be reflected in changes in HRV indices. We hypothesized that periods of high HR would be correlated with low HF power and either a low (reflecting predominantly parasympathetic inhibition) or unchanged (combined sympathetic stimulation and parasympathetic inhibition) LF power, with the LF-to-HF ratio either increasing or staying constant. We tested this hypothesis by evaluating changes in HR, HF power, LF power, and the LF-to-HF ratio in horses during road transportation for 21 hours and compared the relationships of these variables with HR and with each other during this period and with the same responses during a 24-hour control period of stall rest.

Materials and Methods

Animals—Five healthy Thoroughbreds (2 males and 3 females; 2 years old; mean ± SD weight, 501 ± 38 kg) were studied. All horses were clinically normal as determined by physical examination findings and CBC determination prior to all measurements. Horses had been housed in individual stalls (3.6 × 3.6 m) with straw bedding and turned out in 2ha pastures for approximately 7 h/d before being transported. Horses were fed a concentrate 3 times a day at 6:00 AM, 4:00 PM, and 7:00 PM (the third feeding was lighter than the others) and had ad libitum access to hay and water through the day. Although horses had experience with short road transportation episodes of < 1 hour, they had not been transported for longer periods. Three horses had received no previous exercise training; 2 horses had been trained for a period of 10 months but had stopped all training for a period of 40 days prior to the experiment.

Measurements during stall rest—Electrocardiograms were recorded for a period of 24 hours from each horse while it was in its usual stall the day before horses were transported. The mean ambient temperature and the mean relative humidity were 10.3°C and 94%, respectively. Electrocardiograms were recorded with a base-apex lead and a Holter-type electrocardiographa starting at 1:00 PM. Horses wore a surcingle around their girth to which the recorder was attached.

Measurements during transportation—Horses were transported by road in a 9-horse diesel-powered van (only loaded with 5 horses for the experiment) of the type typically used by the Japan Racing Association. They faced forward and were restricted with their heads cross-tied loosely in the van with the floor covered by a rubber mat. Horses were transported from the Hidaka Training and Research Center of the Japan Racing Association in Urakawa, Hokkaido Prefecture, to the Equine Research Institute of the Japan Racing Association in Utsunomiya, Tochigi Prefecture, a total distance of approximately 1,200 km. The van left the Hidaka Training and Research Center at 1:00 PM and arrived at the Equine Research Institute at 10:00 AM the following day. The temperature and relative humidity at departure were 10.5°C and 71%, respectively, and on arrival were 16.7°C and 88%. During the trip, from 10:00 PM to 2:00 AM (approx 4 hours) the van was on a 7,000-ton automobile ferry moving across the Tsugaru Strait between the islands of Hokkaido and Honshu. The seas were fairly calm during the ferry passage. The van was stopped, and the horses were rested for 30 minutes from 5:00 to 5:30 PM and from 6:00 to 6:30 AM and before and after the ferry trip (from 9:30 to 10:00 PM and from 2:00 to 2:30 AM). They were given water during each rest period and fed pelleted feed before loading onto the ferry (9:30 PM). Electrocardiograms were recorded continuously during transportation from 1:00 PM to 10:00 AM with the use of identical equipment and techniques used for recording in stalls.

Data analysis—Recorded ECGs were analyzed with an ECG processor analyzing systemb as previously described19 that used software running on a computer to evaluate ECGs stored on disk at 250 Hz. The program first detected R-waves and calculated the R-R interval tachogram. Noise that the computer detected as R-waves was eliminated manually by visual inspection and examining any data that fell outside 70% to 130% of the mean. A spline curve was fit to the tachogram from which data sets of 512 points were reevaluated at 200-millisecond intervals with the sampling window advanced 20 seconds for each data set. These values were selected as a compromise to balance the need for a large time series for accuracy versus the need for reasonably short recording periods.2 We applied each set of data to a Hamming window and fast Fourier transform to obtain the power spectrum density of the fluctuation and calculated LF power and HF power as the areas under the curves within their frequency ranges for each hour of the experiment. We set LF power at 0.01 to 0.07 Hz and HF power at 0.07 to 0.6 Hz as previously determined for horses by Kuwahara et al19 on the basis of frequencies at which the major spectral components of HRV and the maximum coherence between HRV and respiratory and blood pressure variabilities occurred. The HR, LF power, HF power, and LF-to-HF ratio were obtained from each recording.

Statistical analysis—Values are expressed as mean ± SE of the hourly means of the 5 horses. Comparisons for each variable between stall rest and road transportation were made by use of a 2-way repeated-measures ANOVA with treatment and time of day as factors. Differences between individual time points were determined with the use of the Student-Newman-Keuls multiple comparison test.

Variables were evaluated for changes over time with the use of least squares linear regression analysis and for diurnal rhythmicity by use of nonlinear regression analysis (Levenberg-Marquardt algorithm) to fit an equation of the following form:

article image

where Y is the value of the dependent variable; × the number of hours into the protocol; and a, m, p, and q are fitted parameters that determine amplitude, frequency, temporal offset, and magnitude offset of the response curve, respectively. To determine whether this relationship fit the data better than a linear estimate, the ratio of the error mean squares of the linear and nonlinear regression analyses was calculated, and with the appropriate degrees of freedom, this F statistic was used to determine whether an improvement was found in fit by use of the sinusoidal function. An ANCOVA was used to determine whether slopes of linear regression lines were significantly different from each other.

Associations between variables were evaluated by calculating the Pearson product moment correlation coefficient. Because the variables were correlated with each other to different extents, the relative influences of the 3 variables (HF power, LF power, and LF-to-HF ratio) on HR were determined by use of backward stepwise linear regression analysis.

All calculations were made with the use of a software program.c Data were evaluated to ensure normality and homoscedasticity. Alpha was set at a level of 0.05. A value of P < 0.05 was considered significant.

Results

Clinical findings—No horses had any signs of medical abnormalities before, during, or following transportation as indicated by physical examination or measurement of rectal temperature. Second-degree atrioventricular block appeared in the ECG of 1 horse during stall rest for 2 to 16 beats•h−1 from 9:00 PM to 12:00 midnight; however, these arrhythmias were not observed during transport. No other arrhythmias were observed in any horses.

HR and HRV versus time—The HR during stall rest had regular variation throughout the day (Figure 1), with a sinusoidal function fitting the data significantly (R2 = 0.825; P < 0.001) better than a linear relationship; values for amplitude, frequency, temporal offset, and magnitude offset of the response curve were 2.43, −20.3, 11.1, and 37.5, respectively. The HR during stall rest varied from a high of 41.0 beats•min−1 (11:00 AM) to a low of 34.6 beats•min−1 (3:00 AM). During road transportation, HR decreased linearly with time (R2 = 0.666) with a slope of −0.499 beats•min−1•h−1 from a high of 56.0 beats•min−1 (1:00 PM) to a low of 37.2 beats•min−1 (9:00 AM). Because the datum for the first hour of road transportation was more than 3.5 SEs from the predicted regression analysis results and outside the 99% confidence interval, we evaluated the possibility that the point was an outlier by fitting a second linear regression line to the road transportation data excluding that point. This resulted in a significantly (P < 0.001) better fit to the data (R2 = 0.814) and indicated that following the first hour of transportation, HR decreased during road transportation at a rate of 0.375 beats•min−1•h−1. The HR was significantly higher during road transportation (43.2 ± 0.8 beats•min−1) than stall rest (37.7 ± 0.4 beats•min−1), and significant differences also existed as a result of time and time × treatment interaction.

Figure 1—
Figure 1—

A—Mean ± SEM HR as a function of time of day in 5 Thoroughbreds during 24 hours of rest in a stall (open circles) or 21 hours of road transportation (closed circles). B—High-frequency power (0.07 to 0.6 Hz) from Fourier analysis of HR power spectra as a function of time of day. C—Low-frequency power (0.01 to 0.07 Hz) from Fourier analysis of HR power spectra as a function of time of day. D—Low frequency-to-high frequency ratio as a function of time of day. Notice the results of nonlinear (stall rest) and linear (road transportation) regression analysis (solid lines), linear regression analysis fitted to stall rest data (dotted line), and linear regression analysis fitted to all but first transportation datum (a possible outlier; dashed line). Periods are indicated (horizontal bars) during transportation when the vehicle was stopped and horses were rested and given water (R), food (F), or both or were at sea on an automobile ferry.

Citation: American Journal of Veterinary Research 67, 3; 10.2460/ajvr.67.3.455

The HF power during stall rest (Figure 1) also had a significantly (R2 = 0.658; P < 0.001) better fit with a sinusoidal function than with linear regression analysis with values for amplitude, frequency, temporal offset, and magnitude offset of the response curve of 161, 20.5, 43.3, and 502, respectively. During road transportation, HF power decreased linearly (R2 = 0.456; P < 0.001) with a slope of −5.74 milliseconds2•h−1. The HF power was significantly (P = 0.006) lower during road transportation (235 ± 12 milliseconds2) than during stall rest (467 ± 29 milliseconds2).

The LF power during stall rest (Figure 1) fit a sine function significantly (R2 = 0.357; P = 0.029), although the fit was not significantly (P = 0.09) better than that of linear regression analysis, even though the fit of the linear regression line itself was not significant (R2 = 10−4; P = 0.96). Regression parameters were −247, −21.7, 8.97, and 1,728 for amplitude, frequency, temporal offset, and magnitude offset of the response curve, respectively. During road transportation, LF power decreased linearly (R2 = 0.438; P < 0.001) with a slope of −35.3 milliseconds2•h−1. The LF power was significantly (P = 0.045) lower during road transportation (839 ± 72 milliseconds2) than during stall rest (1676 ± 59 milliseconds2), with significant (P = 0.024) treatment × time interaction.

The LF-to-HF ratio was not correlated with time during stall rest (Figure 1) and was only weakly correlated during road transportation (R2 = 0.293; P = 0.011), with a slope of −0.0772 LF-to-HF ratio•h−1. The LF-to-HF ratios during road transportation (3.93 ± 0.19) were not significantly different (P = 0.585) from those during stall rest (4.44 ± 0.13).

HRV indices and LF-to-HF ratio—The HF power was correlated with the LF-to-HF ratio (R2 = 0.263; P = 0.017) only during road transportation, not during stall rest (Figure 2). The LF power was also correlated with the LF-to-HF ratio (R2 = 0.714; P < 0.001) only during road transportation. The LF power was correlated with HF power (Figure 3) during road transportation (R2 = 0.679; P < 0.001) and stall rest (R2 = 0.312; P = 0.005). The slope of the relationship of LF power versus HF power was significantly (P < 0.001) steeper during road transportation (slope = 5.17) than during stall rest (slope = 1.13).

Figure 2—
Figure 2—

Top—High-frequency power as a function of LF-to-HF ratio in 5 Thoroughbreds during stall rest (open circles) or during road transportation (solid circles). Bottom—Low-frequency power as a function of LF-to-HF ratio. Notice linear regression results for road transportation (solid lines) and nonsignificant regression analysis results for stall rest (dotted lines). Data are plotted with LF-to-HF ratio as the independent variable to facilitate comparing HF and LF power correlations.

Citation: American Journal of Veterinary Research 67, 3; 10.2460/ajvr.67.3.455

Figure 3—
Figure 3—

Low-frequency power as a function of HF power in 5 Thoroughbreds during stall rest (open circles) or during road transportation (solid circles). Notice linear regression analysis results for stall rest and road transportation data (solid lines).

Citation: American Journal of Veterinary Research 67, 3; 10.2460/ajvr.67.3.455

HRV indices versus HR—The HF power was correlated with HR during road transportation (R2 = 0.725; P < 0.001) but not during stall rest (Figure 4). The LF power was also correlated with HR during road transportation (R2 = 0.802; P < 0.001) and was also weakly inversely correlated during stall rest (R2 = 0.229; P = 0.018). The LF-to-HF ratio was only correlated with HR during road transportation (R2 = 0.570; P < 0.001).

Figure 4—
Figure 4—

Top—High-frequency power as a function of HR in 5 Thoroughbreds during stall rest (open circles) or during road transportation (solid circles). Middle—Low-frequency power as a function of HR. Bottom—Low frequency-to-high frequency ratio as a function of HR. Notice the linear regression analysis results for road transportation (solid lines) and nonsignificant regression analysis results for stall rest (dotted lines). Data are plotted with HR as the independent variable to facilitate comparison between HRV indices.

Citation: American Journal of Veterinary Research 67, 3; 10.2460/ajvr.67.3.455

We identified HRV indices that were primary determinants of HR by performing backward stepwise regression analysis on HR as a function of HF power, LF power, and the LF-to-HF ratio. Results indicated that HR during road transportation was primarily determined by HF power (P < 0.001) with a significant contribution from the LF-to-HF ratio (P < 0.001) and no contribution from LF power (P = 0.12). The multiple linear regression equation of HR = 25.3 + (0.0452 HF) + (1.86 LF:HF) fit the road transportation data well (R2 = 0.863; P < 0.001; Figure 5).

Figure 5—
Figure 5—

Heart rate as a function of HF power and LF-to-HF ratio during road transportation as determined by backward stepwise linear regression analysis. Response surface is shown as a grid overlaying data points with drop lines.

Citation: American Journal of Veterinary Research 67, 3; 10.2460/ajvr.67.3.455

The HR during stall rest was best described by LF power (P = 0.004) and the LF-to-HF ratio (P = 0.025) with no contribution from HF power (P = 0.14). The multiple linear regression equation of HR = 38.2 − (0.00359 LF) + (1.25 LF:HF) fit the stall rest data (R2 = 0.397; P = 0.005; Figure 6).

The combined data sets for road transportation and stall rest were plotted with HR depicted as an independent variable (Figure 7) for the sake of more clearly showing the extent of overlap or separation of HF power and LF power at common HRs. The response surfaces did not overlap for any common HR.

Figure 6—
Figure 6—

Heart rate as a function of LF power and LF-to-HF ratio during stall rest as determined by backward stepwise linear regression analysis. Response surface is shown as a grid overlaying data points with drop lines.

Citation: American Journal of Veterinary Research 67, 3; 10.2460/ajvr.67.3.455

Figure 7—
Figure 7—

Interrelationship between HR, HF power, and LF power during stall rest (open circles) and road transportation (solid circles). Separate response surfaces for stall rest and road transportation do not intersect despite significant overlap of HRs.

Citation: American Journal of Veterinary Research 67, 3; 10.2460/ajvr.67.3.455

Discussion

Power spectrum analysis of HR has been shown to be an index of the relative magnitude of autonomic nervous tone in dogs and humans.1–3 Studies in resting subjects with autonomic blockade indicate that HF power is strongly associated with parasympathetic tone, whereas sympathetic and parasympathetic tone appear to influence LF power. The LF-to-HF ratio has been suggested as an index of cardiac sympathovagal balance in humans.2,4

Horses may have a slightly different pattern of HRV relationships than these species. Studies that use autonomic blockade with atropine, propanolol, or both in horses found that atropine alone increased HR and decreased HF power and LF power, propanolol alone increased LF power with no change in HR, and atropine administered following propanolol decreased HF power and LF power in a dose-dependent manner, with HR increasing at the highest doses.19,20 These responses were interpreted as indicating that horses have particularly high parasympathetic tone at rest, consistent with clinical observation of common arrhythmias in normal resting horses that are not considered pathologic (eg, second-degree heart block). However, administration of propanolol increased LF power, the opposite of what would be expected with sympathetic blockade, and had no effect on HR.19 This suggests that sympathetic tone plays little role in determining HR at rest in horses, and raises questions as to the extent to which LF power is influenced by sympathetic tone in horses, at least at rest. Hamlin et al21 suggested that parasympathetic activity alone was primarily responsible for determining HR up to 110 beats•min−1 in horses after they evaluated HR responses to increases or decreases in systemic pressure produced by phenylephrine or nitroglycerin injected during a control period, after β-adrenergic receptor blockade produced with propanolol, after vagal efferent blockade produced with atropine, and after blockade of β-adrenergic and vagal efferent activity.

Our purpose in conducting this study was to test the hypothesis that changes in LF power, HF power, and LF-to-HF ratio would explain changes in HR during the stress of prolonged transportation of horses and to evaluate whether such changes might provide a more sensitive and perhaps quantitative indicator of stress than crude indices (eg, HR alone or plasma cortisol concentrations). We tested the hypothesis by first collecting HR and HRV data from horses in a control situation, while they stayed in the box stalls to which they were accustomed to being housed. Keeping them in familiar surroundings should have resulted in diurnal HR and HRV patterns associated with minimum stress. Loading them into a vehicle and subjecting them to 21 hours of transportation according to a typical transportation protocol by the Japan Racing Association for long-distance hauling of horses was expected to elicit changes in autonomic nervous response that might be associated with stress and the immune suppression that many horses appear to have when transported.

Magnitudes of HR, HF power, LF power, and LF- to-HF ratio measured at rest in untrained 2-year-old Thoroughbreds22,23 are similar to this study’s values recorded between 1:00 and 5:00 PM to factor out diurnal influence. Kuwahara et al22 and Ohmura et al23 reported HRs that were slightly higher and LF-to-HF ratios slightly lower than in this study.

The diurnal rhythms observed in HR, HF power, and LF power during stall rest were expected on the basis of previous studies,22,24,25 although the high correlations with the regression equations were surprising, considering the small sample size. The extremely high HR value recorded during the first hour of road transportation is typical of horses loaded into a transport vehicle and the initial part of a journey.9,10,12 The HR overlapped for nearly half of the stall rest and a third of the road transportation data.

The HF power was lower during road transportation compared with stall rest, as hypothesized with parasympathetic inhibition. However, counterintuitively, HF power decreased with time during road transportation even as HR was also decreasing. The LF power was also lower during road transportation than during stall rest, again consistent with parasympathetic inhibition with no (or less) sympathetic stimulation to attenuate it. However, LF power also decreased with time as HR decreased during road transportation. Studies of HRV during various forms of stress in other species have reported reductions in HRV indices whether triggered by posture or psychologic status,18 panic anxiety,26 sepsis,27septic shock,28 endotoxemia,29 chronic hepatic30 or respiratory31 disease, or chronic heart failure.32

Neither HF power nor LF power was correlated with LF-to-HF ratio during stall rest, but both were significantly associated with LF-to-HF ratio during road transportation, suggesting that the determinants of the ratio were more strongly associated with it under the presumably stressful conditions of road transportation than they were during stall rest. The relationship between LF power and HF power was different during road transportation than stall rest. Correlation between LF power and HF power was only about half as strong during stall rest as during road transportation, and the slope of the relationship was nearly 5 times as large during road transportation. This partially explains why LF power was more highly correlated with LF-to-HF ratio during road transportation than HF power, since LF power changed by a much larger amount during road transportation than did HF power.

The relationships between HRV indices and HR are of particular interest in evaluating the effects of transport-associated stress on autonomic responses of horses. All 3 HRV indices were significantly correlated with HR during road transportation, but during stall rest, only LF power was correlated (inversely) with HR, and its association was much weaker than the other variables during road transportation. Inspection of the relationships between HRV indices and HR indicates that despite considerable overlap in the range of HR during stall rest and road transportation, virtually no overlap of HF power, LF power, or LF-to-HF ratio was found within a given value of HR. Values of all 3 HRV indices were below the range of values observed at the same HR during stall rest, despite considerable variability in HRV data during stall rest at all values of HR. This observation strongly implies that HR is controlled by different mechanisms during stall rest and road transportation (eg, altered sinoatrial node sensitivity) such that identical values of HF power, LF power, or LF-to-HF ratio produce higher values of HR during road transportation than during stall rest. Although overinterpretation of HF power and LF power can occur because of their inherent correlation with HR,33 HR was highest in our data when HRV indices were lowest, opposite this bias.

The response surface generated by multiple linear regression analysis revealed that the backward stepwise procedure best fit HRs during road transportation. The R2 value (0.863) suggests that HF power and LF-to-HF ratio accounted for the variance in the data to a remarkable extent, despite the fact that LF power was the HRV index with the highest correlation with HR during road transportation. However, because the HRV parameters are multicollinear, LF power proved to be less valuable than LF-to-HF ratio in determining HR during road transportation when HF power was included in the model.

A similar response surface generated for HR during stall rest revealed that LF power and LF-to-HF ratio were the only significant explanatory variables, but the data were much more variable, and regression analysis explained half as much variability in the data (R2 = 0.397) as did HF power and LF-to-HF ratio during road transportation. Again, multicollinearity among parameters resulted in an insignificant effect of HF power on the model.

The observation that the response surfaces extending across the entire range of HR and HF power for road transportation and stall rest had no intersection suggests that consideration of the multivariate relationship between HRV indices and HR might identify horses that are undergoing stress versus those that are not, even when all horses have identical HRs. It remains to be determined how this relationship might change with the magnitude of stress that horses experience (ie, the gain of the system); however, the separation of these relationships is a potentially valuable tool for identifying and quantifying stress. Such a procedure might require a given horse to be assessed for control values in a low-stress situation (eg, the stall rest treatment we used) to account for individual differences between horses and the effects on HRV as a result of various factors (eg, training22,23 and age).

The results of this study clearly indicate that HRV indices are associated with HR in a different manner during a period of prolonged stress associated with road transportation than during stall rest. Our original hypothesis that HR would increase and HF power would decrease during road transportation was supported, suggesting that parasympathetic tone decreased. However, the fact that HF power continued to decrease as HR decreased over time during road transportation seems paradoxical. Furthermore, we could interpret the decrease in LF power during road transportation as indicating that during stall rest, it was primarily determined by parasympathetic tone with little or no sympathetic component and thus it decreased when parasympathetic tone decreased. However, it also continued to decrease over time as HR decreased. If a component of sympathetic tone is involved in determining HR, it is possible that the decrease in LF power over time reflected a decrease in sympathetic output as the horses accommodated to the prolonged period of transport, but that is speculative. Indeed, it is notable that HF power and LF power decreased by identical magnitude to half their stall rest values during road transportation.

Why HRV indices are so much more highly related to HR during the stress of road transportation than during stall rest may be related to the influence of humoral changes occurring in the horses as part of their response to stress. Either the sensitivity of the autonomic system or the direct effects of circulating catecholamines might alter the response of the sinoatrial node to a given quantity of autonomic stimulation. Further studies will be required to determine what other factors associated with the stress response might be modifying the relationship between HRV indices and HR during stress versus rest.

HR

Heart rate

HRV

HR variability

HF

High frequency

LF

Low frequency

a.

SM-60, Fukuda Denshi Co Ltd, Tokyo, Japan.

b.

Softron Co Ltd, Tokyo, Japan.

c.

SigmaStat, version 3.0, SPSS Inc, Chicago, Ill.

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Contributor Notes

Portions of this study were presented at the Second International Conference on Transport of Horses by Road, Sea and Air, Hartpury, England, July 2003.

Supported in part by the California Center for Equine Health with funds from the California Satellite Wagering Fund, Oak Tree Racing Foundation, and private donors.

Dr. Jones.