Heart Rate Variability in Sport Performance: Do Time of Day and Chronotype Play A Role?

A reliable non-invasive method to assess autonomic nervous system activity involves the evaluation of the time course of heart rate variability (HRV). HRV may vary in accordance with the degree and duration of training, and the circadian uctuation of this variable is crucial for human health since the heart adapts to the needs of di erent activity levels during sleep phases or in the daytime. In the present review, time-of-day and chronotype e ect on HRV in response to acute sessions of physical activity are discussed. Results are sparse and controversial; however, it seems that evening-type subjects have a higher perturbation of the autonomic nervous system (ANS), with slowed vagal reactivation and higher heart rate values in response to morning exercise than morning types. Conversely, both chronotype categories showed similar ANS activity during evening physical tasks, suggesting that this time of day seems to perturb the HRV circadian rhythm to a lesser extent. The control for chronotype and time-of-day e ect represents a key strategy for individual training schedules, and, in perspective, for primary injury prevention. Keywords:HRV; circadian typology; physical activity; orthopaedics; HIIT. 1. Introduction The way in which the cardiovascular system responds to exercise stress has captured the imagination of sport scientists over the past century [1]. During physical activity, critical adjustments are continually made by the cardiovascular system to meet the diver's demands with respect to the musculature and the heart [2]. These dynamic adjustments in cardiac and peripheral vascular control, including their regulation

way in which the cardiovascular system responds to exercise stress has captured the imagination of sport scientists over the past century [1]. During physical activity, critical adjustments are continually made by the cardiovascular system to meet the diver's demands with respect to the musculature and the heart [2]. These dynamic adjustments in cardiac and peripheral vascular control, including their regulation by the autonomic nervous system (ANS), occur in response to rapid changes in the heart rate (HR) and blood pressure. These variations also include circadian variations during the course of the day, which could have either a positive or negative e ect on sport performance [3]. For this reason, understanding the interactions between cardiovascular function, activity of the ANS, chronobiology, biological rhythms, and chronotype allows to us understand the e ects of exercise on human performance. Therefore, the aim of this narrative review is to discuss the circadian pattern of heart rate variability (HRV) and the e ect of time-of-day and chronotype on HRV circadian rhythm in response to acute physical activity 2. Chronobiology, Biological Rhythms, and Chronotype Chronobiology (from three Greek words: “kronos” for time, “bios” for life, and “logos” for study) is the science that objectively studies the biological mechanisms of time structures. Rhythms can be observed at all levels of biologic integration, and show di erent frequencies: (1) the ultradian rhythm J. Clin. Med.2019,8, 723; doi:10.3390 /jcm8050723 /journal/jcm

J. Clin. Med.2019,8, 723 2 of 15 (<20 h; e.g., a full sleep cycle) [4]; (2) circadian rhythm (period between 20 h and 28 h, speci cally relating to biological variations over 24 hours [5–7]); and (3) the infradian rhythms (period>28 h, including circaseptan, circadiseptan, circavigintan, circatrigintan, and circannual rhythms [5,8–10]). Each biological rhythm has speci c quanti able characteristics and usually three di erent parameters are described: (1) acrophase (Ø), which indicates the time interval within which the highest values are observed; (2) amplitude (A), a measure of one half of the extent of rhythmic variation in a cycle; and (3) MESOR, acronym of Midline Estimating Statistic of Rhythm (M), the rhythm-determined mean [10,11]. The existence of human's circadian rhythms is explained by the interaction of several multifactorial systems cooperating at the same time, including exogenous, endogenous, and lifestyle mechanisms [12]. Speci cally, the internal master circadian clock resides within the suprachiasmatic nuclei (SCN) of the anterior hypothalamus [13] and autonomous circadian clocks are present in nearly all tissues [14]. On the other hand, the SCN is also synchronized with the environment by external factors called “zeitgebers” (“time-givers” in German) or “synchronizers”. The primary synchronizer for the human body clock is the light–dark cycle; the light gives information to the SCN, passing from retinal ganglion cells via a direct pathway (the retinohypothalamic tract), leading to a synchronization of the peripheral clocks by neuro-normal signaling [15,16]. In addition, many other variables could play the role of secondary synchronizers, such as physical activity, sleep and meal timing, and/or social routine [6,16]; it has indeed been shown that regular training, intended as chronic exercise, is associated with better nocturnal sleep and with a physiological circadian expression of steroid hormones in healthy and pathological conditions [6,17]. In general, the correct expression of biological rhythms is crucial for body homeostasis since individuals perform optimally when all biological rhythms are in sync [18]. Nevertheless, it is important to highlight that circadian rhythmic expression may largely vary among individuals, and this characteristic is typically de ned as “circadian typology” or “chronotype”. The chronotype is usually evaluated

pathological conditions [6,17]. In general, the correct expression of biological rhythms is crucial for body homeostasis since individuals perform optimally when all biological rhythms are in sync [18]. Nevertheless, it is important to highlight that circadian rhythmic expression may largely vary among individuals, and this characteristic is typically de ned as “circadian typology” or “chronotype”. The chronotype is usually evaluated using self-assessment questionnaires, validated in several forms and countries [19–23], and the most-used and cited questionnaire is the Morningness–Eveningness Questionnaire (MEQ) [24]. There are three di erent chronotypes—morning types (M-types or “larks”), evening types (E-types or “owls”), and neither types (N-types) —that represent an individual's predisposition towards morningness or eveningness [19]. The chronotype distribution is in uenced both by environmental (i.e., latitude and photoperiod at birth) and individual factors, such as sex and age: men are typically E-types while women tend to be M-types, especially before 40 years of age; however, this trend is overturned with advancing age [25], and in general, after the end of adolescence, morningness scores tend to increase with age [26]. Chronotype does not concern just a subjective predisposition; indeed, several studies have shown large bio-psycho-physiological di erences between M-types and E-types in relation to the circadian rhythms of di erent variables. M-types, for instance, use to wake up and go to bed earlier than E-types [27], both during weekend and week days [28], and they display an advanced acrophase of blood melatonin concentrations and rest–activity circadian rhythm by about 02:30 h [19,28]. On the other hand, E-types show delayed acrophases of oral temperature (+2 hours) and serum cortisol (+55 minutes) circadian rhythms as compared to M-types [29,30]. It is also important to note that chronotype can also a ect human cognitive and physical performance [19,31]. It was shown that M-types have greater vigor levels and higher memory task scores in the morning compared to E-types [31,32] and, in addition, morning-oriented subjects registered faster race times in the morning for the half marathon, full marathon, and 200-m swimming trial than the other chronotypes [33,34]. Conversely, people with a strong predisposition toward eveningness reach their best performances

It was shown that M-types have greater vigor levels and higher memory task scores in the morning compared to E-types [31,32] and, in addition, morning-oriented subjects registered faster race times in the morning for the half marathon, full marathon, and 200-m swimming trial than the other chronotypes [33,34]. Conversely, people with a strong predisposition toward eveningness reach their best performances later in the day: E-types seem to have more of an advantage and to be less fatigued in the second part of the day than N- and M-types [35–38]. Therefore, it seems that the chronotype could play a key role in determining the circadian expression of the human body clock in di erent conditions and settings.

J. Clin. Med.2019,8, 723 3 of 15 3. HRV Assessment The HR and circulatory systems are controlled primarily by higher brain centers and cardiovascular control areas in the brain stem through the activity of the ANS, which is composed of sympathetic and parasympathetic nerves. The medulla is the primary site to regulate sympathetic and parasympathetic (vagal) out ow to the heart and blood vessels [39]. The rate and variation of heart beats are the results of a complex interaction between sympathetic and parasympathetic e erent impulse activity in addition to the in uence of sinus node pacemaker properties [40]. The sinoatrial (SA) node is directly and richly innervated by both sympathetic and parasympathetic (vagus) nerve bers, which are continually active; the atrioventricular (AV) node is less a ected. Parasympathetic stimulation hyperpolarizes the SA node, decreasing the rate of spontaneous ring and the cardiac rate. On the other hand, sympathetic nerve endings release norepinephrine and the adrenal medulla releases epinephrine, stimulating the spontaneous ring rate of the SA and increasing cardiac rate. Although both the sympathetic and parasympathetic systems are active at rest, the parasympathetic bers release acetylcholine, which acts to slow the pacemaker potential of the SA node and thus reduces heart rate [39]. Therefore, sympathetic stimulation increases the HR, contractility, and conduction velocity, whereas parasympathetic stimulation has the opposite e ect. In addition, autonomic control of the cardiovascular system is also a ected by baroreceptors, chemoreceptors, muscle a erents, local tissue metabolism, and circulating hormones [1]. Since the ANS is linked with many other physiological systems, its responsiveness may provide useful information about the functional adaptations of the body during and after exercise [1]. One of the most non-invasive reliable methods to assess the ANS activity is to evaluate the time course of heart rate variability (HRV), which is the natural uctuation of HR in time due to internal and external body process [1]. It is usually measured as the standard (or average) deviation from the mean intervals between successive heartbeats (NN intervals or R-R intervals) of all cardiac cycle lengths (R-R intervals for normal sinus beats) over a

the time course of heart rate variability (HRV), which is the natural uctuation of HR in time due to internal and external body process [1]. It is usually measured as the standard (or average) deviation from the mean intervals between successive heartbeats (NN intervals or R-R intervals) of all cardiac cycle lengths (R-R intervals for normal sinus beats) over a given period, from 5 minutes to 24 hours [41]. Originally, HRV was assessed manually from calculations of the mean R-R interval and its standard deviation measured on a short-term electrocardiogram (ECG). Recently advances in recording techniques and innovative smart devices have enabled the quanti cation of autonomic functions. Several algebraic methods and graphs allow us to study and describe the HRV, among which the most used correspond to the methods of the time domain, in which the R-R intervals (in milliseconds) are plotted against time (in seconds) and frequency domain, measuring the frequency at which the length of the R-R intervals changes. Another measurement is the standard deviation of the normal R-R interval, known as the SDNN (ms) index. This measure basically shows how much the HR di ers from the overall daylong mean HR. Yet others have used the standard deviation (SD) index, that is, the mean of the SD computed for each successive 5-min period over 24-h, measuring the variation that occurs within 5-min periods rather than the variation that occurs over longer time intervals. Other measures include pNN50 index (%), which shows the instances per hour in which two consecutive normal R-R intervals di er by more than 50 ms over 24-h; the base of the triangular area under the main peak of the R-R interval frequency distribution diagram obtained from 24-h recording; and the RMSSD (ms) index, the root-mean square of the di erence of successive R-R intervals. Although it is generally accepted that the various methods measuring peak-to-peak variation in cardiac cycle length can be used as an index of parasympathetic activity, information on the changes in both sympathetic and parasympathetic activity of the heart may be obtained only by using spectral analysis. The peak-to-peak

index, the root-mean square of the di erence of successive R-R intervals. Although it is generally accepted that the various methods measuring peak-to-peak variation in cardiac cycle length can be used as an index of parasympathetic activity, information on the changes in both sympathetic and parasympathetic activity of the heart may be obtained only by using spectral analysis. The peak-to-peak variation is usually represented as a tachogram in which the signals sampled at regular are interpolated and synchronized with the QRS complexes of the ECG [1]. Both methods basically measure a random signal. Spectral analysis of the HRV provides information on the di erent statistical components of the signal. It transforms the signal from time to frequency on the x-axis by representing it as a combination of sine and cosine waves, with di erent amplitudes and frequencies which are used to describe its spectral components. This is the classic nonparametric approach for determining rhythmic components and is known as the Fast Fourier transform (FFT). The FFT is an objective method in which the tachogram provides a spectrum

J. Clin. Med.2019,8, 723 4 of 15 of the high frequency power (HF), which is de ned by the energy in the HR power spectrum between 0.15 and 0.40 Hz, evaluating the parasympathetic activity, and the low frequency power (LF), de ned by the energy in the HR spectrum between 0.04 to 0.15 Hz, which de nes both sympathetic and parasympathetic activity [1]. Ultra-low frequency power (ULF, 0.003 Hz) and very low frequency power (VLF, 0.003–0.04 Hz) can also be measured [1]. However, the HR is continuously modulated by non-linear uctuations due to postural changes, physical activity, and multiple interactions with other physiological systems, and it may also be a ected by small perturbations (e.g. premature ventricular contractions, atrioventricular block) [42,43]. These measurements involve the quanti cation of the “chaos” in heart rhythms or the behavior of HRV patterns over di erent time scales (i.e., a few minutes vs. 24 hours). The most common non-linear methods applied to HRV are: (1) the Poicar±plot [44]; (2) approximate entropy [45]; (3) sample entropy [46]; (4) correlation dimension [47]; and (5) detrended uctuation analysis [48] and recurrence plots [49]. Despite the higher computational complexity required, these approaches have recently proven superior in quantifying and mapping non-linear and chaotic ANS activities, as well as in correlating HRV signals to precise psychological states of research subjects [50]. When applying these methods is important to ensure low signal-to-noise ratio, accurate estimation of high-frequency spectrum in short-time recordings, and low variability of signals [51]. It has also been demonstrated that HRV can be a ected by respiration frequency [1,39,41]. Generally, the HRV increases when respiratory frequency decreases. Although respiration greatly a ects the HRV, the absence of standardized models of respiratory frequency makes it di cult to interpret HRV data. According to previous studies, researchers have accepted various respiratory frequency ranges (e.g. from 6 to 15 breath/min). However, it is clear that a self-organized respiratory pattern should be maintained during the recording period [1,39]. Also, it is important that standard protocols and methods be established with athletes with regard to exercise intensity and duration, respiration rate, position

interpret HRV data. According to previous studies, researchers have accepted various respiratory frequency ranges (e.g. from 6 to 15 breath/min). However, it is clear that a self-organized respiratory pattern should be maintained during the recording period [1,39]. Also, it is important that standard protocols and methods be established with athletes with regard to exercise intensity and duration, respiration rate, position of the body during recording, and duration of recording [1]. 4. HRV Circadian Rhythm Among all the physiological function showing a circadian rhythmicity, the cardiovascular system displays a marked daily rhythm in most of the physiological parameters, including HR and blood pressure [52]. HR circadian rhythm starts to raise around awakening time or soon after the beginning of the individual's activity; it reaches the acrophase between 10:00 and 12:00 h and maintains a lower level during the night [53]. This HR uctuation is crucial for human health since it guarantees that the heart adapts to the needs of di erent activity levels during sleep phases or daytime by decreasing or increasing the cardiac output [53,54]; as a consequence, HRV shows marked circadian variations. These daily uctuations of the ANS [55,56] that re ect the sympathovagal balance activity are commonly found at rest in healthy subjects [57]. In general, HRV parameters tend to increase during the nighttime and to decrease during the day, showing however a larger variability around awakening when HR changes rather abruptly from the nightly low to the much higher daily values [55,56]. The actual transition usually starts earlier, but any anticipatory rise preceding awakening and the transition in the evening is smoother and slower [58,59]. It has also been observed that age is able to a ect the HRV circadian rhythm. Due to the immaturity of the ANS and the increased sleep time, children under 12 months old do not register a signi cant HRV rhythm [58]. On the contrary, increasing age corresponds to a reduced power of the 24-hour HRV [60], a decline in e erent vagal cardiac tone, and a decreased beta-adrenergic responsiveness [61–64]. Autonomic derailments have also been reported to augment cardiovascular degeneration in

ANS and the increased sleep time, children under 12 months old do not register a signi cant HRV rhythm [58]. On the contrary, increasing age corresponds to a reduced power of the 24-hour HRV [60], a decline in e erent vagal cardiac tone, and a decreased beta-adrenergic responsiveness [61–64]. Autonomic derailments have also been reported to augment cardiovascular degeneration in the aging population, shifting the autonomic balance toward sympathetic dominance [65–67]. Some pathological conditions (i.e., ischemic cardiac disease) are able to a ect the ANS function with the amplitude of the HRV circadian rhythm that can be altered, attened, or nearly absent [59,60,68,69], with altered acrophases and MESOR values. Indeed, the lowest HRV nadir that is observed in the morning [62] corresponds to the period of highest incidence of ventricular tachycardia and sudden death [70–72]. This unhealthy circadian pattern has

J. Clin. Med.2019,8, 723 5 of 15 been already observed in patients a ected by other pathological conditions, such as diabetes, obesity, metabolic syndrome, and cancer [7], and this further con rms the need to maintain and correct the circadian system. For these reasons, it is reasonable to believe that HRV circadian rhythm is linked to wake time and daily physical activity (PA) levels, although results are still sparse and this question has not been fully studied. In line with this hypothesis, it has been shown that there are a series of changes in the cardiovascular system soon after waking and commencing activity, which include an increase in HR, blood pressure, plasma catecholamine levels, and renin activities [73]. In the next chapter, we will discuss the e ect of time-of-day and chronotype on HRV circadian rhythm in response to acute PA. The changes in HRV have also been studied to explore sympathovagal balance during sleep [74]. It has been observed that slow-wave sleep is characterized by decreased LF with a relative predominance of HF as compared to a waking state [75]. Moreover, it was suggested that rapid eye movement sleep is characterized by an HRV pattern with increased linear variability as compared to slow-wave sleep and wakefulness [75]. In addition, Vigo et al., [76] demonstrated that state slow-wave sleep is characterized with increased HRV, whereas rapid eyes movements (REM) sleep is associated with increased linear HRV in all frequency components. Speci cally, they observed that during the slow-wave cycle, HRV was characterized by high-entropy VLF and increased relative amplitude in the HF component with rapid eye movement sleep that were indistinguishable from the wake phase with respect to nonlinear HRV, and were associated with increased linear HRV globally and all its frequency components. 5. HRV and Physical Exercise During physical exercise the vagal tone is withdrawn and HR is regulated principally by adrenergic activity [77]. The mechanism of the exercise-induced tachycardia involves parasympathetic and spinal sympathetic re ex circuits. Thus, both the sympathetic and parasympathetic arms of the ANS play a pivotal role during exercise. Changes in HRV in response

The review explores how heart rate variability is influenced by time of day and individual chronotype during physical activity.