Cardiac Vagal Control and Depressive Symptoms: The Moderating Role of Sleep Quality

Resting vagally-mediated heart rate variability in the laboratory is associated with momentary negative affect and emotion regulation in daily life

Vagally-mediated heart rate variability (vmHRV) is a physiological index reflecting parasympathetic activity that has been linked to emotion regulation (ER) capacity. However, very limited research has examined associations of physiological indices of regulation such as vmHRV with emotional functioning in daily life. The few studies that exist have small samples sizes and typically focus on only a narrow aspect of ER or emotional functioning. In this study, we examined associations between vmHRV assessed in the laboratory and emotional/mental health functioning in daily life using a 7-day ecological momentary assessment design in 303 adult community participants. We hypothesized that higher resting vmHRV would be associated with higher positive affect (PA), lower negative affect (NA), less affective variability, greater well-being, fewer dysphoria symptoms, greater use of engagement ER strategies, and less use of avoidance ER strategies, as assessed in daily life. Results revealed that higher resting vmHRV in the laboratory (as indexed by both high frequency heart rate variability, HF-HRV, and the root mean of successive square deviations between heart beats, RMSSD) was significantly associated with less frequent use of avoidance ER strategies in daily life. Theoretical and clinical implications are discussed, including the association of vmHRV with negatively valenced, rather than positively valenced, daily life experiences.

Comprehensive evaluation of machine learning algorithms for predicting sleep-wake conditions and differentiating between the wake conditions before and after sleep during pregnancy based on heart rate variability

Introduction

Perinatal women tend to have difficulties with sleep along with autonomic characteristics. This study aimed to identify a machine learning algorithm capable of achieving high accuracy in predicting sleep-wake conditions and differentiating between the wake conditions before and after sleep during pregnancy based on heart rate variability (HRV).

Methods

Nine HRV indicators (features) and sleep-wake conditions of 154 pregnant women were measured for 1 week, from the 23rd to the 32nd weeks of pregnancy. Ten machine learning and three deep learning methods were applied to predict three types of sleep-wake conditions (wake, shallow sleep, and deep sleep). In addition, the prediction of four conditions, in which the wake conditions before and after sleep were differentiated-shallow sleep, deep sleep, and the two types of wake conditions-was also tested.

Results and Discussion

In the test for predicting three types of sleep-wake conditions, most of the algorithms, except for Naïve Bayes, showed higher areas under the curve (AUCs; 0.82-0.88) and accuracy (0.78-0.81). The test using four types of sleep-wake conditions with differentiation between the wake conditions before and after sleep also resulted in successful prediction by the gated recurrent unit with the highest AUC (0.86) and accuracy (0.79). Among the nine features, seven made major contributions to predicting sleep-wake conditions. Among the seven features, "the number of interval differences of successive RR intervals greater than 50 ms (NN50)" and "the proportion dividing NN50 by the total number of RR intervals (pNN50)" were useful to predict sleep-wake conditions unique to pregnancy. These findings suggest alterations in the vagal tone system specific to pregnancy.

Sleep and Daily Positive Emotions – Is Heart Rate Variability a Mediator?

Abstract. Sleep quality is considered a basic dimension of emotional health. The psychophysiological mechanisms underlying the associations between sleep quality and positive emotions are still largely unknown, yet autonomic regulation may play a role. This study employed a two-day ecological momentary assessment methodology in a sample of young adults to investigate whether subjective sleep quality reported in the morning was associated with daily positive emotional experience and whether this association was mediated by heart rate variability (HRV), a measure of cardiac vagal tone. Sleep quality was assessed using an electronic sleep diary upon awakening, while resting HRV and positive emotions were inspected at random times throughout the day using photoplethysmography and an electronic diary, respectively. Relevant confounding variables such as smoking, alcohol intake, and physical exercise between each measurement were also assessed. The sample included 121 participants (64.8% females, Mage = 25.97 ± 5.32 years). After controlling for relevant confounders including health behaviors and psychiatric comorbidities, mediation analysis revealed that greater sleep quality positively predicted daily HRV (β = .289, p < .001) which, in turn, had a direct influence on positive emotions (β = .244, p = .006). Also, sleep quality directly predicted positive emotional experience (β = .272, p = .001). Lastly, the model showed an indirect effect between sleep quality and positive emotions via HRV (β = .071, 95% BCI [.011, .146]). Results support the view of HRV as a process variable linking sleep to positive emotions. Experimental data is needed to consolidate the present findings.

Heart Rate Variability, Sleep Quality, and Depression in the Context of Chronic Stress

BACKGROUND

Disrupted sleep quality is one of the proposed mechanisms through which chronic stress may lead to depression. However, there exist significant individual differences in sleep reactivity, which is the extent to which one experiences sleep disturbances in response to stress.

PURPOSE

The aim of the current study was to investigate whether low high-frequency heart rate variability (HRV), as a psychophysiological marker of poor emotional and physiological arousal regulation, predicts stress-related sleep disturbances associated with greater risk of depression symptoms.

METHODS

Using a chronic caregiving stress model, 125 mothers of adolescents with developmental disorders and 97 mothers of typically developing adolescents had their resting HRV and HRV reactivity recorded and completed a measure of depressive symptoms, as well as a 7 day sleep diary to assess their sleep quality. A moderated mediation model tested whether sleep quality mediated the association between chronic stress exposure and depressive symptoms and whether HRV moderated this mediation.

RESULTS

After controlling for participant age, body mass index, ethnicity, socioeconomic status, and employment status, poor sleep quality mediated the association between chronic stress and depressive symptoms. Resting HRV moderated this indirect effect such that individuals with lower HRV were more likely to report poorer sleep quality in the context of chronic stressor exposure, which, in turn, was related to greater depressive symptoms.

CONCLUSIONS

Lower HRV, a potential biomarker of increased sleep reactivity to stress, is associated with greater vulnerability to stress-related sleep disturbances, which, in turn, increases the risk for elevated depressive symptoms in response to chronic stress.

Trait mindfulness and the mental and physical health of caregivers for individuals with cancer

BACKGROUND

Mindfulness plays a role in moderating the negative mental and physical health outcomes associated with caregiving. The aims of this study were to examine the relationship between trait mindfulness and the (1) psychological functioning, (2) health behaviors, (3) and physical health of caregivers for individuals diagnosed with cancer.

METHODS

Caregivers completed a battery of questionnaires and examinations assessing sociodemographic characteristics, trait mindfulness, depression, perceived stress, caregiver stress, sleep, diet, physical activity, tobacco use, alcohol use, blood pressure, and BMI. Demographics and cancer diagnostics were collected for the individuals whom caregivers supported. Linear regression, multivariate analyses, and moderator analyses were performed.

RESULTS

Of the 78 caregivers, the mean age was 63.9 (S.D.=13.1); 59% identified as female; 97% identified as White. Regression analyses indicated that caregivers who reported higher levels of trait mindfulness reported significantly less perceived stress (b= -4.38, SE= 0.88, p <.001), lower levels of depression (b= -3.74, SE= 1.10, p = .001), greater caregiver quality of life (b= -9.05, SE=2.12, p < .001), better sleep quality (b= -0.98, SE=0.44, p = 0.03), and lower rates of tobacco use (b= -10.12, SE= 3.43, p =.003). Trait mindfulness was not significantly related to diet, alcohol use, blood pressure, or BMI.

CONCLUSIONS

Higher levels of trait mindfulness are associated with positive mental and physical health measure for caregivers. Future research would benefit from further examining mindfulness-based interventions and their impacts in mitigating the negative toll of caregiving in the context of cancer.

Cardiac Vagal Control, Regulatory Processes and Depressive Symptoms: Re-Investigating the Moderating Role of Sleep Quality

Lower cardiac vagal control (CVC), which is often understood as an indicator for impaired regulatory processes, is assumed to predict the development of depressive symptoms. As this link has not been consistently demonstrated, sleep quality has been proposed as a moderating factor. However, previous studies were limited by non-representative samples, cross-sectional data, and focused on CVC as a physiological indicator for impaired regulatory processes, but neglected corresponding subjective measures. Therefore, we investigated whether sleep quality moderates the effects of CVC (quantified by high-frequency heart rate variability) and self-reported regulatory processes (self- and emotion-regulation) on concurrent depressive symptoms and on depressive symptoms after three months in a representative sample (N = 125). Significant interactions between CVC and sleep quality (in women only), as well as self-/emotion-regulation and sleep quality emerged, whereby higher sleep quality attenuated the relation between all risk factors and current depressive symptoms (cross-sectional data). However, there were no significant interactions between those variables in predicting depressive symptoms three months later (longitudinal data). Our cross-sectional findings extend previous findings on sleep quality as a protective factor against depressive symptoms in the presence of lower CVC and subjective indices of impaired regulatory processes. In contrast, our conflicting longitudinal results stress the need for further investigations.