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Sleep and Circadian Regulation of the Autonomic Nervous System
Abstract
Sleep and the autonomic nervous system (ANS) are intimately connected. The ANS is under the influence of circadian and sleep-dependent modulation. Forced desynchrony and constant routine protocols indicate strong circadian influences on heart rate (HR) and cardiac vagal activity, which fluctuate across 24 hours, with HR being lower, and vagal activity higher, during the nocturnal period. Sleep also influences ANS activity: during non-rapid-eye-movement (NREM) sleep, sympathetic activity is lower and vagal functioning is higher, compared to rapid-eye-movement (REM) sleep, where ANS activity is more similar to wakefulness. A change in ANS innervation of the heart and vasculature drives the wake-to-sleep reductions in blood pressure, HR, and systemic vascular resistance. The reduction in cardiovascular activity during sleep, prominent during NREM sleep, plays a key role in maintaining cardiovascular health, providing a “cardiovascular holiday.” Sleep-dependent as well as circadian regulation of vagal activity is evident very early in life and persists across adulthood. There is some evidence of sex differences in sleep-dependent vagal activity in adolescents as well as female hormone effects on nocturnal ANS measures, although further work is needed to determine the significance of these effects.
... Similarly, NAA is a dynamic process that involves complex interactions between various factors, including circadian rhythms (Hayter et al., 2021), sleep architecture (Gula et al., 2004) through the impact of sleep stages on arrhythmogenesis (Verrier & Josephson, 2009), respiratory events, and autonomic nervous system (ANS) responses (de Zambotti & Baker, 2021;Gula et al., 2004). ...
... Furthermore, sleep apnea-related arrhythmias, including atrial fibrillation and ventricular arrhythmias, may be more likely during sleep due to nocturnal hypoxaemia and altered autonomic control (Gami et al., 2004;Mehra et al., 2006). The autonomic nervous system is profoundly affected by the sleep-wake cycle, with its activity fluctuating throughout the night in response to transitions between sleep stages (de Zambotti & Baker, 2021;Mander et al., 2017). Moreover, ageing plays a key role in nocturnal ANS dysfunction, which is associated with the development of cardiovascular disease and may impact atrial fibrillation susceptibility (Fajemiroye et al., 2018). ...
Nocturnal arrhythmia avalanche (NAA) episodes, characterised by transient non‐sustained cardiac arrhythmias during sleep, have been demonstrated as a predictor of adverse cardiovascular events. However, their dynamics and association with sleep architecture and events remain unclear. While generalised linear models (GLM) have captured sleep‐disordered breathing (SDB) dynamics, their application to NAA remains underexplored. This study explored whether changes in sleep architecture contribute to nocturnal arrhythmias and if the impact of sleep stages, SDB, and arousal events on these arrhythmias varies by demographic factors. We analysed 7341 ECG recordings from the multi‐ethnic study of atherosclerosis (MESA) and the sleep heart health study (SHHS) datasets. R‐R intervals were divided into 10‐min periods to detect NAA, defined as a 30% drop from baseline followed by recovery to 90% of baseline. A GLM framework was developed to characterise NAA episodes as functions of SDB, sleep arousal events, sleep stages, and prior NAA episodes. The GLM analysis revealed that NAA occurrence was 18% and 30% higher during non‐rapid eye movement (NREM) light sleep compared with deep sleep in SHHS ( p < 0.001) and MESA ( p < 0.001), respectively. SDB events increased the NAA risk in 34% of participants, and arousals in 29%. In SHHS, the impact of SDB on NAA was 5% greater in men ( p = 0.018), while the arousal effects were more pronounced in those over 75, highlighting the role of demographic factors in modulating arrhythmia risk. These findings demonstrate the utility of the GLM framework in modelling the dynamics of nocturnal arrhythmias and their associations with sleep disruptions and architecture.
... For example, romantic relational aggression is associated with exaggerated fight or flight responses to a conflict discussion (sympathetic activation and parasympathetic withdrawal) [153], whereas relationship depth and low conflict are associated with greater nocturnal diastolic blood pressure dipping [155]. Likewise, sleep quality and the ANS are intimately connected [156]. For example, it has been shown that shifts in the sympathovagal balance toward sympathetic dominance during sleep contribute to decreased sleep maintenance and more disturbances in the sleep architecture of healthy individuals [157]. ...
Although a significant body of research has revealed associations between romantic relationship experiences and sleep quality, there has not been clarity regarding the mechanisms underlying such associations. Toward this end, we review the existing studies that have tested mechanisms linking romantic relationship experiences to sleep quality. Guided by both theory and existing research, we organize our review around five key categories of mechanisms that may explain associations between romantic relationship experiences and sleep quality: emotional/affective responses, self-perceptions, social perceptions, self-regulation, and biological functioning. Our review of the literature indicates strong evidence in support of the mediating effects of emotional/affective mechanisms (e.g. emotions and mood states) in explaining associations between various aspects of romantic relationships (e.g. relationship satisfaction, partner conflicts, and attachment orientation) and sleep quality. Although there is ample theoretical support for the other mechanisms proposed, and although all proposed mechanisms have been separately linked to both romantic relationship experiences and sleep quality, few studies have directly tested them, pointing to profitable directions for future research. Understanding underlying mechanisms will enable the development of wise, process-based interventions that target specific mechanisms to improve couple members’ sleep quality and romantic relationship functioning.
... There is a fast-growing body of publications showing the complex relationship between pain conditions and activity of ANS centres [25]. There are many examples of this co-existence in people with diseases of various systems: cardiovascular [26]; respiratory [27,28]; digestive [29,30]; genitourinary [31,32]; immune [33]; thermoregulation [34]; cerebral circulation and headaches [35][36][37]; sleep and circadian rhythms [38,39]. Many of the above publications and similar are observational studies (and rarely prospective) or reviews. ...
The role of the autonomic nervous system (ANS) in chronic pain (CP) and in its chronicity is considered secondary and reactive to the nociceptive processes in the somatic nervous system (SomNS). However, research and clinical data strongly suggest the opposite. The ANS is an ancient, complex and ample part of the nervous system. It serves and controls visceral organs and somatic tissues. The ANS takes part in all aspects of all types of pain and influences its mechanisms at both peripheral and central levels. In this chapter we bring together the evidence from biomedical disciplines and clinical practice to support an alternative theory which contradicts the traditional views on the subject. We also raise questions which require further research to consolidate facts, advance our knowledge and improve treatment strategies for CP. The importance of this topic is difficult to overestimate because of the significant impact of CP on society and the lack of understanding, efficient therapy or cure.
To investigate differences in polysomnography (PSG) parameters and heart rate variability (HRV) during the initial 3-h sleep period in patients with mild, moderate, and severe obstructive sleep apnea syndrome (OSA). According to the apnea–hypopnea index, patients were divided into 3 groups: mild, moderate, and severe (n = 23, 59, and 94, respectively). PSG was performed, and HRV (frequency domain analysis), sleep stage (S1, S2, S3, REM, and waking), and sleep fragmentation index (SFI) were measured during the initial 3-h sleep periods. The total S1 time was significantly longer in the severe group than in the mild and moderate groups (p < 0.001). The severe group had significantly shorter total S2 and S3 times than the mild (p = 0.014, p < 0.001) and moderate (p = 0.034, p = 0.029) groups did. The SFI was significantly greater in the severe group than in the mild and moderate groups (p < 0.001, p = 0.008). The high-frequency component (HF) of the HRV showed no significant differences except that it was significantly smaller during S3 in the moderate group than in the mild group (p = 0.026). Compared with those with mild/moderate status, patients with severe OSA have shallower sleep and a higher SFI, suggesting poorer sleep quality. Although HF during S3 was significantly smaller in the moderate group, it did not significantly differ between the mild and severe groups, suggesting that the parasympathetic nervous system might compensate for humoral and hypoxemic abnormalities in patients with severe OSA.
Background
The rapid advancement in wearable solutions to monitor and score sleep staging has enabled monitoring outside of the conventional clinical settings. However, most of the devices and algorithms lack extensive and independent validation, a fundamental step to ensure robustness, stability, and replicability of the results beyond the training and testing phases. These systems are thought not to be feasible and reliable alternatives to the gold standard, polysomnography (PSG).
Materials and methods
This validation study highlights the accuracy and precision of the proposed heart rate (HR)-based deep-learning algorithm for sleep staging. The illustrated solution can perform classification at 2-levels (Wake; Sleep), 3-levels (Wake; NREM; REM) or 4- levels (Wake; Light; Deep; REM) in 30-s epochs. The algorithm was validated using an open-source dataset of PSG recordings (Physionet CinC dataset, n = 994 participants, 994 recordings) and a proprietary dataset of ECG recordings (Z3Pulse, n = 52 participants, 112 recordings) collected with a chest-worn, wireless sensor and simultaneous PSG collection using SOMNOtouch.
Results
We evaluated the performance of the models in both datasets in terms of Accuracy (A), Cohen’s kappa (K), Sensitivity (SE), Specificity (SP), Positive Predictive Value (PPV), and Negative Predicted Value (NPV). In the CinC dataset, the highest value of accuracy was achieved by the 2-levels model (0.8797), while the 3-levels model obtained the best value of K (0.6025). The 4-levels model obtained the lowest SE (0.3812) and the highest SP (0.9744) for the classification of Deep sleep segments. AHI and biological sex did not affect scoring, while a significant decrease of performance by age was reported across the models. In the Z3Pulse dataset, the highest value of accuracy was achieved by the 2-levels model (0.8812), whereas the 3-levels model obtained the best value of K (0.611). For classification of the sleep states, the lowest SE (0.6163) and the highest SP (0.9606) were obtained for the classification of Deep sleep segment.
Conclusion
The results of the validation procedure demonstrated the feasibility of accurate HR-based sleep staging. The combination of the proposed sleep staging algorithm with an inexpensive HR device, provides a cost-effective and non-invasive solution deployable in the home environment and robust across age, sex, and AHI scores.
Heart rate variability (HRV) is a reliable technique to evaluate autonomic activity and shows marked changes across a night of sleep. Previous nighttime sleep findings report changes in HRV during non-rapid eye movement sleep (NREM), which have been associated with cardiovascular health benefits. Daytime sleep, however, has been linked with both positive and negative cardiovascular outcomes. Yet, no studies have directly compared HRV profiles during an ecologically-valid daytime nap in healthy, well-rested adults to that of nighttime sleep. Using a within-subjects design, 32 people took a daytime nap and slept overnight in the lab at least one week apart; both sleep sessions had polysomnography, including electrocardiography (ECG), recorded. We measured inter-beat intervals (RR), total power (TP), low frequency power (LF; .04–.15 Hz), and high frequency power (HF; .15–.40 Hz) components of HRV during NREM and rapid eye movement (REM) sleep. Compared to the nap, we found longer RR intervals and decreased heart rate during the night for both Stage 2 and SWS and increased TP, LF and HF power during nighttime Stage 2 sleep only; however, no differences in the LFHF ratio or normalized HF power were found between the nap and the night. Also, no differences in REM sleep between the nap and night were detected. Similar relationships emerged when comparing the nap to one cycle of nighttime sleep. These findings suggest that longer daytime naps, with both SWS and REM, may provide similar cardiovascular benefits as nocturnal sleep. In light of the on-going debate surrounding the health benefits and/or risks associated with napping, these results suggest that longer daytime naps in young, healthy adults may support cardiac down-regulation similar to nighttime sleep. In addition, napping paradigms may serve as tools to explore sleep-related changes in autonomic activity in both healthy and at-risk populations.
A substantial number of women experience sleep difficulties in the approach to menopause and beyond, with 26% experiencing severe symptoms that impact daytime functioning, qualifying them for a diagnosis of insomnia. Here, we review both self-report and polysomnographic evidence for sleep difficulties in the context of the menopausal transition, considering severity of sleep complaints and links between hot flashes (HFs) and depression with poor sleep. Longitudinal population-based studies show that sleep difficulties are uniquely linked with menopausal stage and changes in follicle-stimulating hormone and estradiol, over and above the effects of age. A major contributor to sleep complaints in the context of the menopausal transition is HFs, and many, although not all, HFs are linked with polysomnographic-defined awakenings, with HF-associated wake time contributing significantly to overall wakefulness after sleep onset. Some sleep complaints may be comorbid with depressive disorders or attributed to sleep-related breathing or movement disorders, which increase in prevalence especially after menopause, and for some women, menopause, age, and environmental/behavioral factors may interact to disrupt sleep. Considering the unique and multifactorial basis for sleep difficulties in women transitioning menopause, we describe clinical assessment approaches and management options, including combination treatments, ranging from cognitive behavioral therapy for insomnia to hormonal and nonhormonal pharmacological options. Emerging studies suggest that the impact of severe insomnia symptoms could extend beyond immediate health care usage and quality of life issues to long-term mental and physical health, if left untreated in midlife women. Appropriate treatment, therefore, has immediate benefit as well as advantages for maintaining optimal health in the postmenopausal years.
To validate measures of sleep and heart rate (HR) during sleep generated by a commercially-available activity tracker against those derived from polysomnography (PSG) in healthy adolescents. Sleep data were concurrently recorded using FitbitChargeHR™ and PSG, including electrocardiography (ECG), during an overnight laboratory sleep recording in 32 healthy adolescents (15 females; age, mean ± SD: 17.3 ± 2.5 years). Sleep and HR measures were compared between FitbitChargeHR™ and PSG using paired t-tests and Bland-Altman plots. Epoch-by-epoch analysis showed that FitbitChargeHR™ had high overall accuracy (91%), high sensitivity (97%) in detecting sleep, and poor specificity (42%) in detecting wake on a min-to-min basis. On average, FitbitChargeHR™ significantly but negligibly overestimated total sleep time by 8 min and sleep efficiency by 1.8%, and underestimated wake after sleep onset by 5.6 min (p < 0.05). Within FitbitChargeHR™ epochs of sleep, the average HR was 59.3 ± 7.5 bpm, which was significantly but negligibly lower than that calculated from ECG (60.2 ± 7.6 bpm, p < 0.001), with no change in mean discrepancies throughout the night. FitbitChargeHR™ showed good agreement with PSG and ECG in measuring sleep and HR during sleep, supporting its use in assessing sleep and cardiac function in healthy adolescents. Further validation is needed to assess its reliability over prolonged periods of time in ecological settings and in clinical populations.
Objective
To quantify the impact of objectively recorded hot flashes on objective sleep in perimenopausal women.
Design
Cross-sectional study. Participants underwent 1–5 laboratory-based polysomnographic recordings for a total of 63 nights, including sternal skin-conductance measures, from which 222 hot flashes were identified according to established criteria. Data were analyzed with hierarchical mixed-effect models and Spearman's rank correlations.
Setting
Sleep laboratory.
Patient(s)
Thirty-four perimenopausal women (age ± SD: 50.4 ± 2.7 years).
Intervention(s)
None.
Main Outcome Measure(s)
Perceived and polysomnographic sleep measures (sleep quality, amount of time spent awake after sleep onset, and number of awakenings). Subjective (frequency and level of bother) and objective (frequency and amount of hot flash–associated awake time) hot-flash measures.
Result(s)
Women had an average of 3.5 (95% confidence interval: 2.8–4.2, range = 1–9) objective hot flashes per night. A total of 69.4% of hot flashes were associated with an awakening. Hot flash–associated time awake per night was, on average, 16.6 minutes (95% confidence interval: 10.8–22.4 minutes), which accounted for 27.2% (SD 27.1) of total awake time per night. Hot flash–associated time awake, but not hot flash frequency, was negatively associated with sleep efficiency and positively associated with waking after sleep onset. In addition, self-reported wakefulness correlated with hot flash–associated waking, suggesting that women's estimates of wakefulness are influenced by the amount of time spent awake in association with hot flashes during the night. Having more perceived and bothersome hot flashes was correlated with more perceived wakefulness and awakenings and more objective hot flash–associated time awake and hot-flash frequency.
Conclusion(s)
The presence of physiological hot flashes accounts for a significant proportion of total objective time awake during the night in perimenopausal women.
Objective:
Little is known about the impact of hot flashes on cardiac autonomic regulation, particularly vagal control. Therefore, we assessed the cardiac autonomic profile associated with physiological hot flashes occurring in undisturbed sleep.
Methods:
Eleven perimenopausal women (45-56 y) had overnight laboratory recordings of polysomnography, electrocardiography, and skin conductance. Eighteen hot flashes that occurred in stable non-rapid eye movement sleep undisturbed by arousals were analyzed. Heart rate variability measures were obtained for three consecutive 2-minute windows starting from 4 minutes before (baseline and preflash periods) to 2 minutes after the onset of hot flashes (hot flash period).
Results:
Heart rate increased by, on average, 4 beats/minute with the occurrence of a hot flash compared with both baseline (P < 0.001) and preflash (P < 0.001). High-frequency power was reduced, reflecting a decrease in vagal activity, at the onset of a hot flash compared with baseline (P < 0.001) and preflash (P < 0.001). There was no change in sympathovagal balance with the onset of a hot flash. The magnitude of the hot flash (ie, skin conductance amplitude) was associated with increased heart rate (r = 0.78, P < 0.001) and decreased vagal tone (r = -0.56, P = 0.014).
Conclusions:
Physiological hot flashes per se, recorded during undisturbed sleep periods and independent of any arousals, are associated with increased heart rate and decreased cardiac autonomic vagal activity. These data support the hypothesis that the parasympathetic branch of the autonomic nervous system is involved in the cardiac response to a hot flash.
The accurate measurement, prediction and treatment of high blood pressure (BP) are essential issues in the management of hypertension. Ambulatory blood pressure monitoring (ABPM) has been shown to be superior to clinic BP measurements as ABPM can provide the following important information: (i) the mean BP levels, (ii) the diurnal variation in BP and (iii) the short-term BP variability. Among these parameters, there is increasing evidence that the mean nocturnal BP level is the most sensitive predictor of cardiovascular morbidity and mortality. Furthermore, several studies have shown that less nocturnal BP dipping, defined as less nocturnal BP decline relative to daytime BP, or a high night-day BP ratio was associated with poor prognosis irrespective of the 24-hour BP levels. These findings can be interpreted in at least two ways: namely, high nocturnal BP or less nocturnal BP dipping might be not only a potent risk factor for cardiovascular disease (CVD), but also a marker of pre-existing or concurrent diseases that can lead to nocturnal BP elevation. In this review, we consider the clinical utility of ABPM and in particular focus on the nocturnal BP levels or nocturnal BP dipping as a potent risk factor for CVD. In addition, the clinical management of high nocturnal BP and blunted nocturnal BP dipping with antihypertensive medications is discussed.
Normal sleep has a profound effect on the cardiovascular system, reducing cardiovascular activity throughout non-rapid eye movement sleep; changes that are modified and augmented by circadian system influence. There is also evidence that sleep-initiated changes in autonomic balance may in turn modify the development of sleep within a night, particularly the development of slow wave sleep. It is assumed that the cardiovascular changes that accompany sleep reflect a functional aspect of sleep, although the precise functional role has not been agreed upon. Nevertheless, there is good evidence that the cardiovascular changes that occur during normal sleep are beneficial for the cardiovascular system. Arousals from sleep, which are common even in normal sleep, are associated with a surge in activity in cardiorespiratory systems, with marked effects on the sleep-related pattern of cardiovascular activity when they occur frequently. Despite the importance of this aspect of sleep, controversy remains as to both the nature of the activation response and the circumstances under which it is elicited. The concept that sleep-related changes in cardiovascular activity are beneficial leads to the corollary that sleep disturbance would result in adverse cardiovascular consequences. While there is strong empirical evidence for such a relationship, it remains unclear whether this is a direct effect or, as has been suggested recently, the effect of disturbed sleep is mediated via stress-related modification of neuroendocrine systems.
The study goal was to investigate autonomic activity with heart rate variability analysis during different sleep stages in males and females.
The study utilized a 2 Groups (males, females) x 4 States (waking, stage 2 sleep, stage 4 sleep, rapid-eye movement sleep) mixed design with one repeated, within-subjects factor (i.e., state).
The study was carried out in the sleep laboratory of the Thomas N. Lynn Institute for Healthcare Research.
Twenty-four healthy adults (fourteen females and ten males).
NA.
All participants underwent polysomnographic monitoring and electrocardiogram recordings during pre-sleep waking and one night of sleep. Fifteen-minute segments of beat-to-beat heart rate intervals during waking, stage 2 sleep, stage 4 sleep, and REM sleep were subjected to spectral analysis. Compared to NREM sleep, REM sleep was associated with decreased high frequency (HF) band power, and significantly increased low frequency (LF) to (HF) ratio. Compared to females, males showed significantly elevated LF/HF ratio during REM sleep. Males also demonstrated significantly decreased HF band power during waking when compared to females. No significant sleep- or gender-related changes in LF band power were found.
The results confirmed changes in autonomic activity from waking to sleep, with marked differences between NREM and REM sleep. These changes were primarily due to stage-related alterations in vagal tone. REM sleep was characterized by increased sympathetic dominance, secondary to vagal withdrawal. The data also suggested gender differences in autonomic functioning during waking and sleep, with decreased vagal tone during waking and increased sympathetic dominance during REM sleep in the males.
Adolescence is marked by dramatic changes in sleep. Older adolescents go to bed later, have an increased preference for evening activities, and sleep less than younger adolescents. This behavior change is driven by external factors, notably increased pressures from academic, social, and extracurricular activities and by biological circadian factors. There are also substantial changes in sleep architecture across adolescence, with dramatic declines in slow wave sleep, and slow wave activity (delta, ~ 0.5-4.5 Hz). These changes are associated with underlying changes in brain structure and organization, with a decrease in synaptic density likely underlying the reduction in high amplitude slow waveforms. While changes in sleep across adolescence are a normal part of development, many adolescents are getting insufficient sleep and are consequently, less likely to perform well at school, more likely to develop mood-related disturbances, be obese, and are at greater risk for traffic accidents, alcohol and drug abuse.
Aging is commonly associated with decreased sleep quality and increased periodic breathing (PB) that can influence heart rate variability (HRV). Cardiac autonomic control, as inferred from HRV analysis, was determined, taking into account the sleep quality and breathing patterns. Two groups of 12 young (21.1 +/- 0.8 years) and 12 older (64.9 +/- 1.9 years) volunteers underwent electroencephalographic, cardiac, and respiratory recordings during one experimental night. Time and frequency domain indices of HRV were calculated in 5-min segments, together with electroencephalographic and respiratory power spectra. In the elderly, large R-R oscillations in the very-low frequency (VLF) range emerged, that reflected the frequency of PB observed in 18% of the sleep time. PB occurred more frequently during rapid eye movement sleep (REM) sleep and caused a significant (P < 0.02) increase in the standard deviation of normal R-R intervals (SDNN) and absolute low-frequency (LF) power. With normal respiratory patterns, SDNN, absolute VLF, LF, and high frequency (HF) power fell during each sleep stage (P < 0.01) compared with young subjects, with no significant sleep-stage dependent variations. An overall decrease (P < 0.01) in normalized HF/(LF + HF) was observed in the elderly, suggesting a predominant loss of parasympathetic activity which may be related to decreased slow-wave sleep duration. These results indicate that two distinct breathing features, implying different levels of autonomic drive to the heart, influence HRV in the elderly during sleep. The breathing pattern must be considered to correctly interpret HRV in the elderly.
Sleep is crucial for the proper functioning of bodily systems and for cognitive and emotional processing. Evidence indicates that sleep is vital for health, well-being, mood, and performance. Consumer sleep technologies (CSTs), such as multisensory wearable devices, have brought attention to sleep and there is growing interest in using CSTs in research and clinical applications. This article reviews how CSTs can process information about sleep, physiology, and environment. The growing number of sensors in wearable devices and the meaning of the data collected are reviewed. CSTs have the potential to provide opportunities to measure sleep and sleep-related physiology on a large scale.
Hot flashes (HFs) are a hallmark of menopause in midlife women. They are beyond bothersome symptoms, having a profound impact on quality of life and wellbeing, and are a potential marker of cardiovascular (CV) disease risk. Here, we investigated the impact on CV functioning of single nocturnal HFs, considering whether or not they were accompanied by arousal from sleep. We investigated changes in heart rate (HR, 542 HFs), blood pressure (BP, 261 HFs), and pre-ejection period (PEP, 168 HFs) across individual nocturnal physiological HF events in women in the menopausal transition or post-menopause (age: 50.7±3.6 years) (n = 86 for HR, 45 for BP, 27 for PEP). HFs associated with arousals/awakenings (51.1%), were accompanied by an increase in systolic (~6 mmHg) and diastolic (~5mmHg) BP and HR (~20% increase), sustained for several minutes. In contrast, HFs occurring in undisturbed sleep (28.6%) were accompanied by a drop in systolic BP and a marginal increase in HR, likely components of the heat dissipation response. All HFs were accompanied by decreased PEP, suggesting increased cardiac sympathetic activity, with a prolonged increase for HFs associated with sleep disturbance. Older age predicted greater likelihood of HF-related sleep disturbance. HFs were less likely to wake a woman in rapid-eye-movement and slow-wave sleep. Findings show that HFs associated with sleep disruption, which are in the majority and more likely in older women, lead to increases in HR and BP, which could have long-term impact on nocturnal CV restoration in women with multiple HFs.
The accurate assessment of sleep is critical to better understand and evaluate its role in health and disease. The boom in wearable technology is part of the digital health revolution and is producing many novel, highly sophisticated and relatively inexpensive consumer devices collecting data from multiple sensors and claiming to extract information about users’ behaviors, including sleep. These devices are now able to capture different bio-signals for determining, for example, heart rate and its variability, skin conductance, and temperature, in addition to activity. They perform 24/7, generating overwhelmingly large datasets (Big Data), with the potential of offering an unprecedented window on users’ health. Unfortunately, little guidance exists within and outside the scientific sleep community for their use, leading to confusion and controversy about their validity and application. The current state-of-the-art review aims to highlight use, validation and utility of consumer wearable sleep-trackers in clinical practice and research. Guidelines for a standardized assessment of device performance is deemed necessary, and several critical factors (proprietary algorithms, device malfunction, firmware updates) need to be considered before using these devices in clinical and sleep research protocols. Ultimately, wearable sleep technology holds promise for advancing understanding of sleep health, however, a careful path forward needs to be navigated, understanding the benefits and pitfalls of this technology as applied in sleep research and clinical sleep medicine.
All species organize behaviors to optimally match daily changes in the environment, leading to pronounced activity/rest cycles that track the light/dark cycle. Endogenous, approximately 24-hour circadian rhythms in the brain, autonomic nervous system, heart, and vasculature prepare the cardiovascular system for optimal function during these anticipated behavioral cycles. Cardiovascular circadian rhythms, however, may be a double-edged sword. The normal amplified responses in the morning may aid the transition from sleep to activity, but such exaggerated responses are potentially perilous in individuals susceptible to adverse cardiovascular events. Indeed, the occurrence of stroke, myocardial infarction, and sudden cardiac death all have daily patterns, striking most frequently in the morning. Furthermore, chronic disruptions of the circadian clock, as with night-shift work, contribute to increased cardiovascular risk. Here we highlight the importance of the circadian system to normal cardiovascular function and to cardiovascular disease, and identify opportunities for optimizing timing of medications in cardiovascular disease.
Sleep is characterized by coordinated cortical and cardiac oscillations reflecting communication between the central (CNS) and autonomic (ANS) nervous systems. Here, we review fluctuations in ANS activity in association with CNS-defined sleep stages and cycles, and with phasic cortical events during sleep (e.g., arousals, K-complexes). Recent novel analytic methods reveal a dynamic organization of integrated physiological networks during sleep and indicate how multiple factors (e.g., sleep structure, age, sleep disorders) affect "CNS-ANS coupling". However, these data are mostly correlational and there is a lack of clarity of the underlying physiology, making it challenging to interpret causality and direction of coupling. Experimental manipulations (e.g., evoking K-complexes or arousals) provide information on the precise temporal sequence of cortical-cardiac activity, and are useful for investigating physiological pathways underlying the CNS-ANS coupling. With the emergence of new analytical approaches and a renewed interest in ANS and CNS communication during sleep, future work may reveal novel insights into sleep and cardiovascular interactions during health and disease, in which coupling could be adversely impacted.
Purpose:
We assessed sex- and age-dependent differences in a cross-sectional analysis of cardiac autonomic nervous system (ANS) regulation during sleep in adolescents.
Methods:
Nocturnal heart rate (HR) and heart rate variability (HRV) metrics, reflecting ANS functioning, were analyzed across the night and within undisturbed rapid eye movement (REM) and non-REM sleep in 149 healthy adolescents (12-22 years; 67 female) from the National Consortium on Alcohol and Neurodevelopment in Adolescence.
Results:
Nocturnal HR was slower in older, more pubertally advanced boys than in younger boys. In girls, HR did not vary according to age or maturity, although overall HRV and vagal modulation declined with age. Although younger boys and girls had similar HR, the male-female HR difference increased by ~2.4 bpm every year (p < .01, higher in older girls). Boys and girls showed expected increases in total HRV across the night but this within-night "recovery" was blunted in girls compared with boys (p < .05). Also, the non-REM and REM difference in HR was greater in girls (p < .01). Models exploring a role of covariates (sleep, mood, reproductive hormones, activity) in influencing HR and HRV showed few significant effects, apart from sedentary activity (higher in older girls), which partially mediated the sex × age interaction in HR.
Conclusions:
Sex-related differences in cardiac ANS function emerge during adolescence. The extent to which sex-age divergences in ANS function are adaptive or reflect underlying sex-specific vulnerability for the development of psychopathology and other health conditions in adolescence needs to be determined.
Introduction:
We analyzed the frequency spectrum of two neonatal sleep stages, namely active sleep and quiet sleep, and the relationship between these sleep stages and autonomic nervous activity in 74 newborns and 16 adults as a comparison.
Method:
Active and quiet sleep were differentiated by electroencephalogram (EEG) patterns, eye movements, and respiratory wave patterns; autonomic activity was analyzed using the RR interval of simultaneously recorded electrocardiogram (ECG) signals. Power values (LFa, absolute low frequency; HFa, absolute high frequency), LFa/HFa ratio, and the values of LFn (normalized low frequency) and HFn (normalized high frequency) were obtained. Synchronicity between the power value of HFa and the LFa/HFa ratio during active and quiet sleep was also examined by a new method of chronological demonstration of the power values of HFa and LFa/HFa.
Results:
We found that LFa, HFa and the LFa/HFa ratio during active sleep were significantly higher than those during quiet sleep in newborns; in adults, on the other hand, the LFa/HFa ratio during rapid eye movement (REM) sleep, considered as active sleep, was significantly higher than that during non-REM sleep, considered as quiet sleep, and HFa values during REM sleep were significantly lower than those during non-REM sleep. LFn during quiet sleep in newborns was significantly lower than that during active sleep. Conversely, HFn during quiet sleep was significantly higher than that during active sleep. Analysis of the four classes of gestational age groups at birth indicated that autonomic nervous activity in a few preterm newborns did not reach the level seen in full-term newborns. Furthermore, the power value of HFa and the LFa/HFa ratio exhibited reverse synchronicity.
Conclusion:
These results indicate that the autonomic patterns in active and quiet sleep of newborns are different from those in REM and non-REM sleep of adults and may be develop to the autonomic patterns in adults, and that parasympathetic activity is dominant during quiet sleep as compared to active sleep from the results of LFn and HFn in newborns. In addition, in some preterm infants, delayed development of the autonomic nervous system can be determined by classifying the autonomic nervous activity pattern of sleep stages.
The current study investigated both sympathetic and vagal autonomic patterns during a daytime sleep in 25 healthy adults (23.2 ± 2.4 years). Pre-ejection period (PEP; related inversely to beta-adrenergic sympathetic activity), the interval between consecutive R-waves (RR) and frequency-domain heart rate variability (HRV) were computed during pre-nap wakefulness and undisturbed sleep stages. Results showed sleep-related changes in RR and HRV measures, whereas PEP decreased significantly from pre-nap to sleep, showing no differences across sleep stages. Moreover, pre-nap PEP and HFnu (the normalized unit of the high-frequency component of HRV) were associated negatively with sleep latency and wake after sleep onset. These results indicate a marked autonomic output reduction during daytime sleep, with different stage-dependent fluctuations for sympathetic and vagal activity. Importantly, pre-nap autonomic activity seems to modulate subsequent sleep quality.
Insomnia is considered a hyperarousal disorder, in which several psychophysiological domains including the autonomic nervous system (ANS) are over-activated, potentially contributing to increased risk for cardiovascular (CV) disease. Here, we aimed to determine whether insomnia that develops in the context of the transition to menopause (menopausal transition insomnia, MTI) is similarly characterized by autonomic arousal. We also took into account modulation of the ANS by the hormonal changes of the menstrual cycle, a factor that has not previously been considered in studies on insomnia. Twenty one women with insomnia (49.0 ± 3 y) and 25 controls (48.8 ± 2.6 y), also in the menopausal transition, had overnight laboratory-based polysomnographic recordings, including electrocardiograph, during the follicular and/or luteal (progesterone ≥ 3 ng ml−1) phases of the menstrual cycle, with 21 women having recordings in both phases. Nocturnal time and frequency-domain heart rate variability (HRV) measures were calculated. Heart rate (HR) was significantly elevated (by ∼4bpm) in MTI compared to controls in both follicular and luteal phases, across hours of the night, including during undisturbed periods of NREM and REM sleep (p < 0.05). A higher HR tended to be associated with lower frequency- and time-domain vagal HRV indices in MTI compared with controls. In both groups, HR was significantly higher and total and high frequency HRV measures were lower in the luteal phase compared to the follicular phase (p < 0.05). In addition, REM compared to NREM sleep was characterized by increased HR coupled with decreased vagal modulation and increased sympathovagal balance (p < 0.01). Insomnia in the menopausal transition is characterized by nocturnal autonomic hyperarousal during both follicular and luteal phases of the menstrual cycle, which could be a factor in the etiology of MTI as well as a potential CV risk factor.
In most persons, blood pressure (BP) rises slowly during late sleep; increases rapidly upon morning awakening and commencement of diurnal activity; exhibits two -- morning and afternoon/early evening -- daytime peaks; minor midday nadir, and decline during nighttime sleep by 10 to 20% in systolic BP and somewhat lesser amount in diastolic BP relative to wake-time means. Nyctohemeral cycles of ambient temperature, light, noise and behaviorally driven food, liquid, salt, and stimulant consumption, mental/emotional stress, posture, and physical activity intensity plus circadian rhythms of wake/sleep, pineal gland melatonin synthesis, autonomic and central nervous, hypothalamic-pituitary-adrenal, hypothalamic-pituitary-thyroid, renin-angiotensinaldosterone, renal hemodynamic, endothelial, vasoactive peptide, and opioid systems constitute the key regulators and determinants of the BP 24h profile. Environmental and behavioral cycles are believed to be far more influential than circadian ones. However, the facts that the: i) BP 24h pattern of secondary hypertension, e.g., diabetes and renal disease, is characterized by absence of BP fall during sleep, and ii) scheduling of conventional long-acting medications at bedtime, rather than morning, results in much better hypertension control and vascular risk reduction, presumably because highest drug concentration coincides closely with the peak of most key circadian determinants of the BP 24h profile, indicates endogenous rhythmic influences are of greater importance than previously appreciated.
Measurement of heart rate variability (HRV) is an established method to assess the activity of the autonomic nervous system. The aim of this review was to examine the link between HRV, reproductive life stages and menopausal hormone therapy. A literature review was performed using the Medline database. Based on title and abstract, 45 studies were extracted out of 261 citations screened. Due to different study designs and evaluation methods, HRV indices were not directly comparable. Qualitative comparisons in between the vast majority of studies, however, demonstrated a decrease of the vagal dominance on the heart from the follicular to the luteal cycle phase, although some studies asserted no change. The intake of oral contraceptives appeared not to alter the vagal modulation of the heart. All investigations agreed on a decline of HRV towards higher sympathetic control after menopause. Different menopausal hormone therapy approaches showed a supporting impact of estrogen on HRV in most studies. A combined therapy of estrogen and progestogens revoked this benefit. Further research is needed to demonstrate how this process might be attenuated by different menopausal hormone therapies.
In healthy individuals, a reduction in cardiovascular output and a shift to parasympathetic/vagal dominant activity is observed across nocturnal sleep. This cardiac autonomic profile, often measured by heart rate variability (HRV), has been associated with significant benefits for the cardiovascular system. However, little is known about the autonomic profile during daytime sleep. Here, we investigated the autonomic profile and short-term reliability of HRV during daytime naps in 66 healthy young adults. Participants took an 80–120 min polysomnographically recorded nap at 1:30 pm. Beat-by-beat RR interval values (RR), high (HF) and low frequency (LF) power, total power (TP), HF normalized units (HFnu), and the LF/HF ratio were obtained for 5 min during presleep wakefulness and during nap sleep stages (N2, N3, REM). A subsample of 37 participants took two additional naps with 2 weeks between recordings. We observed lengthening of the RR, higher HF and HFnu, and lower LF/HF during NREM, compared with REM and wake, and a marked reduction of LF and TP during N3. Intraclass correlation coefficients highlighted a short-term stability of RR and HF ranging across sleep stages between 0.52–0.76 and 0.52–0.80, respectively. Our results suggest that daytime napping in healthy young adults is associated with dynamic changes in the autonomic profile, similar to those seen during nocturnal sleep. Moreover, a reliable intraindividual measure of autonomic cardiac activity can be obtained by just a single daytime nap depending on specific parameters and recording purposes. Nap methodology may be a new and promising tool to explore sleep-dependent, autonomic fluctuations in healthy and at-risk populations.
Heart rate variability (HRV) analyses can provide a non-invasive evaluation of cardiac autonomic activity. How autonomic control normally develops in childhood and how this is affected by obesity remains incompletely understood. In this review we examine the evidence that childhood age and weight status influence autonomic control of the heart as assessed using HRV. Electronic databases (Pubmed, EMBASE and Cochrane Library) were searched for studies examining HRV in healthy children from birth to 18 years who adhered to the Task Force (1996) guidelines. Twenty-four studies met our inclusion criteria. Seven examined childhood age and HRV. A reduction in 24-hour LF:HF was reported from birth to infancy (1 year), while overall HRV (SDNN) showed a marked and progressive increase. From infancy to early-to-late childhood (from 12 months to 15 years) LF:HF ratio was reported to decline further albeit at a slower rate, while RMSSD and SDNN increased. Twenty studies examined the effects of weight status and body composition on HRV. In a majority of studies, obese children exhibited reductions in RMSSD (n=8/13), pNN50% (n=7/9) and HF power (n=14/18), no difference was reported for LF (n=10/18), while LF:HF ratio was elevated (n=10/15). HRV changes during childhood are consistent with a marked and progressive increase in cardiac parasympathetic activity relative to sympathetic activity. Obesity disrupts the normal maturation of cardiac autonomic control.
To investigate the influence of menstrual cycle phase and the presence of severe premenstrual symptoms on cardiac autonomic control during sleep, we performed heart rate variability (HRV) analysis during stable non-rapid eye movement (NREM) and REM sleep in 12 women with severe premenstrual syndrome and 14 controls in the mid-follicular, mid-luteal, and late-luteal phases of the menstrual cycle. Heart rate was higher, along with lower high frequency (HF) power, reflecting reduced vagal activity, and a higher ratio of low frequency (LF) to high frequency power, reflecting a shift to sympathetic dominance, in REM sleep compared with NREM sleep in both groups of women. Both groups of women had higher heart rate during NREM and REM sleep in the luteal phase recordings compared with the mid-follicular phase. HF power in REM sleep was lowest in the mid-luteal phase, when progesterone was highest, in both groups of women. The mid-luteal phase reduction in HF power was also evident in NREM sleep in control women but not in women with PMS, suggesting some impact of premenstrual syndrome on autonomic responses to the hormone environment of the mid-luteal phase. In addition, mid-luteal phase progesterone levels correlated positively with HF power and negatively with LF/HF ratio in control women in NREM sleep and with the LF/HF ratio during REM sleep in both groups of women. Our findings suggest the involvement of female reproductive steroids in cardiac autonomic control during sleep in women with and without premenstrual syndrome.
Various techniques have demonstrated that NREM sleep is associated with reduced sympathovagal tone (vagal dominance). The effect is characterized by lowered sympathetic vasomotor tone, downward resetting of the baroreflex, marginally increased BRS, and elevated parasympathetic activity. Because it has not been possible to isolate sympathetic effects on the heart during sleep, the central role of the SNS remains uncertain. It remains unclear whether the change in sympathovagal balance reflects an influence of sleep mechanisms over the ANS, or the reverse; the most likely scenario is that there are reciprocal influences. Sleep deprivation appears to have only minor effects on sympathovagal balance. However, the effects of OSA are substantial and are likely to mediate many pathophysiological processes associated with the disorder.
Background:
The usefulness of heart rate variability (HRV) as a clinical research and diagnostic tool has been verified in numerous studies. The gold standard technique comprises analyzing time series of RR intervals from an electrocardiographic signal. However, some authors have used pulse cycle intervals instead of RR intervals, as they can be determined from a pulse wave (e.g. a photoplethysmographic) signal. This option is often called pulse rate variability (PRV), and utilizing it could expand the serviceability of pulse oximeters or simplify ambulatory monitoring of HRV.
Methods:
We review studies investigating the accuracy of PRV as an estimate of HRV, regardless of the underlying technology (photoplethysmography, continuous blood pressure monitoring or Finapresi, impedance plethysmography).
Results/conclusions:
Results speak in favor of sufficient accuracy when subjects are at rest, although many studies suggest that short-term variability is somewhat overestimated by PRV, which reflects coupling effects between respiration and the cardiovascular system. Physical activity and some mental stressors seem to impair the agreement of PRV and HRV, often to an inacceptable extent. Findings regarding the position of the sensor or the detection algorithm are not conclusive. Generally, quantitative conclusions are impeded by the fact that results of different studies are mostly incommensurable due to diverse experimental settings and/or methods of analysis.
Spectral analysis of fetal heart rate variability is promising for assessing fetal condition. Before using spectral analysis for fetal monitoring it has to be determined whether there should be a correction for gestational age or behavioural state.
Compare spectral values of heart rate variability between near term and post term fetuses during active and quiet sleep.
Case-control. Cases had a gestational age of > or =42 weeks; controls were 36 to 37 weeks. Fetuses were matched for birth weight percentile.
STAN registrations from healthy fetuses. For each fetus one 5-minute segment was selected during active and one during quiet sleep.
Absolute and normalized low (0.04-0.15 Hz) and high frequency power (0.4-1.5 Hz) of heart rate variability.
Twenty fetuses were included. No significant differences were found between cases and controls in absolute (481 and 429 respectively, P=0.88) or normalized low (0.78 and 0.80 respectively, P=0.50) or absolute (41 and 21 respectively, P=0.23) or normalized high frequency power (0.08 and 0.07 respectively, P=0.20) during active state. During rest, normalized low frequency power was lower (0.58 and 0.69 respectively, P=0.03) and absolute (16 and 10 respectively, P=0.04) and normalized high frequency power were higher (0.21 and 0.14 respectively, P=0.01) in cases compared to controls. Absolute and normalized low frequency power were higher during active state compared to rest in both groups (all P values <0.05).
We found sympathetic predominance during active state in fetuses around term. Post term parasympathetic modulation during rest was increased compared to near term.
This article reviews the normal development of sleep in infants, children, and adolescents, with specific focus on both the subjective and objective aspects of sleep. Notably, sleep duration decreases substantially from infancy through adolescence with increased consolidation of sleep to the nighttime period only. Sleep architecture exhibits developmental changes with decreases in slow-wave sleep and increases in stage 2 sleep from childhood through adolescence. Although the development of sleep is a dramatic and relatively rapid process during the first decades of life, changes in sleep continue across the life span.
To assess the separate contributions of the sleep and circadian systems to changes in cardiac autonomic nervous system (ANS) activity, 12 supine subjects participated in two 26-h constant routines, which were counterbalanced and separated by 1 wk. One routine did not permit sleep, whereas the second allowed the subjects to sleep during their normal sleep phase. Parasympathetic nervous system activity was assessed with respiratory sinus arrhythmia as measured from the spectral analysis of cardiac beat-to-beat intervals. Sympathetic nervous system activity was primarily assessed with the preejection period as estimated from impedance cardiography, although the 0.1-Hz peak from the spectral analysis of cardiac beat-to-beat intervals, the amplitude of the T wave in the electrocardiogram, and heart rate were also measured. Respiratory sinus arrhythymia showed a 24-h rhythm independent of sleep, whereas preejection period only showed a 24-h rhythm if sleep occurred. Thus the findings indicate that parasympathetic nervous system activity is mostly influenced by the circadian system, whereas sympathetic nervous system activity is mostly influenced by the sleep system.
Measurements of heart rate variability (HRV) are increasingly used as markers of cardiac autonomic activity.
To examine circadian variation in heart rate and HRV in children.
A total of 57 healthy infants and children, aged 2 months to 15 years, underwent ambulatory 24 hour Holter recording. Monitoring was also performed on five teenagers with diabetes mellitus and subclinical vagal neuropathy in order to identify the origin of the circadian variation in HRV.
The following variables were determined hourly: mean RR interval, four time domain (SDNN, SDNNi, rMSSD, and pNN50) and four frequency domain indices (very low, low and high frequency indices, low to high frequency ratio). A chronobiological analysis was made by cosinor method for each variable.
A significant circadian variation in heart rate and HRV was present from late infancy or early childhood, characterised by a rise during sleep, except for the low to high frequency ratio that increased during daytime. The appearance of these circadian rhythms was associated with sleep maturation. Time of peak variability did not depend on age. Circadian variation was normal in patients with diabetes mellitus.
We have identified a circadian rhythm of heart rate and HRV in infants and children. Our data confirm a progressive maturation of the autonomic nervous system and support the hypothesis that the organisation of sleep, associated with sympathetic withdrawal, is responsible for these rhythms.
Whether antihypertensive drugs offer cardiovascular protection beyond blood pressure lowering has not been established. We aimed to investigate whether pharmacological properties of antihypertensive drugs or reduction of systolic pressure accounted for cardiovascular outcome in hypertensive or high-risk patients.
In a meta-analysis we extracted summary statistics from published reports, and calculated pooled odds ratios for experimental versus reference treatment. We correlated across-trials odd ratios for differences in systolic pressure between groups.
We analysed nine randomised trials comparing treatments in 62605 hypertensive patients. Compared with old drugs (diuretics and b-blockers), calcium-channel blockers and angiotensin converting-enzyme inhibitors offered similar overall cardiovascular protection, but calcium-channel blockers provided more reduction in the risk of stroke (13.5%, 95% CI 1.3-24.2, p=0.03) and less reduction in the risk of myocardial infarction (19.2%, 3.5-37.3, p=0.01). Heterogeneity was significant between trials because of high risk of cardiovascular events on doxazosin in one trial, and high risk of stroke on captopril in another; but systolic pressure differed between groups in these two trials by 2-3 mm Hg. Similar systolic differences occurred in a trial of diltiazem versus old drugs, and in three trials of converting-enzyme inhibitor against placebo in high-risk patients. Meta-regression across 27 trials (136124 patients) showed that odds ratios could be explained by achieved differences in systolic pressure.
Our findings emphasise that blood pressure control is important. All antihypertensive drugs have similar long-term efficacy and safety. Calcium-channel blockers might be especially effective in stroke prevention. We did not find that converting-enzyme inhibitors or a-blockers affect cardiovascular prognosis beyond their antihypertensive effects.
Measurements of the variability in heart rate are increasingly used as markers of cardiac autonomic activity. We sought to establish the development this variability in healthy young infants while sleeping.
We carried out polygraphic studies with electrocardiographic recording in 587 healthy infants aged from 5 to 26 weeks.
We determined several variables over a period of 400 minutes sleeping: mean RR interval, 5 time-domain (SDNN, SDNNi, SDANNi, RMSSD, and pNN50) and 5 frequency-domain indexes (spectral power over 3 regions of interest, total power and low-to-high frequency ratio). Frequency-domain indexes were also assessed separately for the periods of quiet sleep and those of rapid eye movement sleep.
Our data showed a significant correlation between the indexes of heart rate variability and the mean RR interval, the breathing rate, and the corrected age of the infants. We also demonstrated the importance of the maturation of the sleeping patterns.
These data in a large cohort of healthy infants confirm a progressive maturation of the autonomic nervous system during sleep, and may be used to examine the influence of physiological and pathophysiological factors on autonomic control during polygraphic studies.
Heart rate (HR), blood pressure (BP) and autonomic nervous system (ANS) activity vary diurnally, with a reduction in HR and BP, and a shift to vagal dominance during the dark phase. However, the cause of these changes, particularly the relative influence of sleep and circadian mechanisms, remains uncertain. The present study assessed the effect of sleep onset on HR, BP, high frequency (HF) component of heart rate variability (HRV), low frequency/high frequency (LF/HF) ratio and pre-ejection period (PEP). Sleep onset was dissociated from circadian influences by having subjects go to sleep at two different circadian phases, their normal time of sleep onset (normal sleep onset, NSO), and after a delay of 3 h (delayed sleep onset, DSO). The assumption was that changes caused by sleep onset would occur in association with sleep onset, irrespective of its timing, while circadian effects would have a consistent circadian phase and be independent of when sleep onset occurred. Thirteen and 17 subjects were run in the NSO and DSO conditions, respectively. Following a 1-h adaptation period, data collection began 2 h before subjects' normal time of sleep onset and continued until morning awakening. The lights were turned out after 2 h in the NSO condition and 5 h in the DSO condition. Subjects were required to maintain a supine position throughout the experimental sessions. The night-time decrease in HR was found to be due to both sleep onset and a circadian influence, with the circadian component being more prominent. In contrast, the fall in BP was largely due to a sleep onset effect. Increased vagal activity, as reflected in the HF component and a shift to vagal dominance in the LF/HF ratio, appeared to be primarily a function of the sleep system, while sympathetic activity, as assessed by PEP, reflected a circadian influence.
We tested the hypothesis that the reductions of the changes in the respective influence of the cardiac sympathetic and vagal activity control and delta EEG activity with aging alter the interactions between the heart rate variability (HRV) and the delta sleep EEG power band.
A polysomnography was performed on 16 healthy young men and 19 healthy middle-aged men across the first 3 NREM-REM cycles. Spectral analysis was applied to electrocardiogram and electroencephalogram recordings. High Frequency (HF(nu)) of HRV as well as the maximum of cross-spectrum, coherency, gain and phase shifts between HF(nu) and delta sleep EEG power band were compared between both groups.
Young men experienced more deep sleep than middle-aged men (P<0.001). In middle-aged subjects, HF(nu) was lower than the HF(nu) of their younger counterparts (P<0.001), but they showed similar increases during NREM sleep and similar decreases during REM sleep as the young subjects. Cross-spectrum values, coherency, gain and phase shifts between HF(nu) and delta were identical between the two groups. Modifications in HF(nu) show parallel changes and precede changes in delta EEG band by a similar leads of 11+/-6min in young men and 9+/-7 min in middle-aged men (P=0.23).
Reduced changes in the respective influence of the cardiac sympathetic and vagal activity and delta EEG activity with progressive aging do not alter the relationship and phase difference between changes in the relative predominant cardiac vagal activity and delta power in middle-aged men.
Interaction between the cardiac sympathetic and vagal activity with delta EEG activity is maintained in middle-aged men.
Sleep is an important modulator of cardiovascular function, both in physiological conditions and in disease states. In individuals without a primary sleep disorder, sleep may exert significant effects on the autonomic nervous system, systemic hemodynamics, cardiac function, endothelial function, and coagulation. Some of these influences can be directly linked to specific modulatory effects of sleep stages per se; others result from the natural circadian rhythm of various physiological processes. There is a temporal association between physiological sleep and occurrence of vascular events, cardiac arrhythmias, and sudden death. Epidemiological and pathophysiological studies also indicate that there may be a causal link between primary sleep abnormalities (sleep curtailment, shift work, and sleep-disordered breathing) and cardiovascular and metabolic disease, such as hypertension, atherosclerosis, stroke, heart failure, cardiac arrhythmias, sudden death, obesity, and the metabolic syndrome. Finally, sleep disturbances may occur as a result of several medical conditions (including obesity, chronic heart failure, and menopause) and may therefore contribute to cardiovascular morbidity associated with these conditions. Further understanding of specific pathophysiological pathways linking sleep disorders to cardiovascular disease is important for developing therapeutic strategies and may have important implications for cardiovascular chronotherapeutics.
To analyze sex differences in nocturnal vagal tone and cardiac sympathovagal balance during sleep in healthy men and women.
In two groups of healthy, non-obese adults (15 men and 14 women), sleep was polygraphically recorded and heart rate variability was assessed during an awake period prior to sleep and during sleep. Vagal tone was estimated by the high-frequency (HF) power component of heart rate variability, and sympathovagal balance was indexed by the ratio of low-frequency (LF) power to HF power.
As compared to women, men showed decreases in vagal tone and increases in sympathovagal balance. During rapid eye movement (REM) sleep, a withdrawal of vagal tone occurred with an increase in sympathetic dominance. Men showed a greater increase of sympathovagal balance during REM sleep than women. Secondary analyses covarying for differences in reproductive hormone levels, physical activity, and sleep measures did not alter the results.
The marked increase in cardiac sympathetic drive during REM sleep in men has implications for understanding sex differences in the risk of cardiovascular events. Additionally, these data offer a pathway to explain the peak in cardiac arrhythmias and sudden cardiac death seen more often in the morning hours.
In recent years, the role of oestrogen in women's health has been a subject of considerable scientific and popular debate. There is unquestionable evidence that oestrogen has both potent and long‐lasting effects on several vital organ systems, including the cardiovascular system, the autonomic nervous system and, most recently, within the central nervous system itself.
The research and medical community continues to debate whether the benefits of oestrogen therapy outweigh the risks in the treatment of the symptoms of menopause, the attenuation of the risk for cardiovascular insults, such as stroke and heart disease, and even the retardation of the progression of Alzheimer's disease.
The recent evidence provided by the Heart and Estrogen/Progestin Replacement Study (HERS) II clinical trial suggesting that long‐term exposure to combined oestrogen and progestin in post‐menopausal women who have previously had a heart attack or stroke (for secondary prevention) may actually increase their risk of a subsequent cardiovascular insult has further fuelled the debate. However, there remain considerable gaps in our knowledge with respect to the actual mechanisms by which oestrogen exerts its various beneficial effects at the cellular level for the primary prevention of cardiovascular disease. This information is essential if we are to harness the positive aspects of oestrogen therapy in such a manner as to avoid or minimize the associated risks of increased oestrogen exposure in women who we know, with some certainty, to be at an increased risk of cancers of the uterus, cervix and breast tissue.
Sleep affects the control of circulation and respiratory function. Gender and age are also known to have a profound impact on the neural control of circulation. We investigated whether gender affects sleep-related cardiovascular and respiratory responses and whether these vary according to healthy subjects being young or middle-aged.
We studied 32 subjects: 8 women and 8 men aged 20-30 years (young), and 8 women and 8 men aged 50-60 years (middle-aged). Young women were under oral contraceptive therapy and middle-aged women were postmenopausal and not receiving hormonal replacement therapy. One-night polysomnography was used to assess RR variability during non-rapid eye movement (NREM) (stage 2) and rapid eye movement (REM) sleep. Low-frequency (LF) and high-frequency (HF) components, in normalized units (LFnu and HFnu) and LF/HF ratio were calculated on five-minute segments selected across the night and averaged for each sleep stage. The respiration frequency in NREM and REM sleep was also measured. Interaction between gender, age and sleep on autonomic and respiration variables was assessed by 2 x 2 x 2 analysis of variance (ANOVA).
Compared to men, women had a greater NREM-to-REM increment in LFnu (gender-by-state interaction, p<0.01), a greater decrement in HFnu (interaction, p<0.01) and a greater increment in LF/HF (interaction, p<0.05). Women also showed a more pronounced increase in respiratory frequency during REM sleep compared to men in both groups of age (gender-by-state interaction, F=7.1, p<0.05). No gender-by-age-by-state interaction was observed to affect autonomic and respiration variables.
NREM-to-REM excitatory cardiac and respiratory responses are more marked among women compared to men, regardless of their hormonal status and whether they are young or middle-aged.
Standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology
Autonomic activity during human sleep as a function of time and sleep stage
- J Trinder
- J Kleiman
- M Carrington
- S Smith
- S Breen
- N Tan