HRV serves as a comprehensive measure of the regulation of the cardiac autonomic nervous system, encompassing frequency domain, time domain, and nonlinear indices. Frequency domain indicators such as LF、HF、LF/HF, time domain indicators such as SDNN、SDANN、RMSSD、PNN50, and non-linear indicators such as Poincare map and sample entropy are utilized to assess the complexity and non-linear characteristics of HRV. It is widely accepted among scholars that SDNN primarily signifies the overall activity of the autonomic nerve system. SDANN and LF are indicative of sympathetic nerve activity, with their values decreasing as sympathetic nerve tension increases. RMSSD、PNN50 and HF, on the other hand, reflects vagal nerve activity, with its value decreasing as vagal nerve tension reduces. The LF/HF ratio serves as a quantitative measure for assessing the functional equilibrium of the sympathetic and vagus nerves. The interpretation of HRV indices remains inconclusive. A study suggests that while LF is modulated by sympathetic nerve function, it is not advisable to rely solely on LF to gauge sympathetic nervous system activity, as it is also impacted significantly by vagus nerve activity and other factors. LF/HF can offer insights into the regulatory function of the autonomic nervous system, however, its accuracy is compromised by nonlinear relationships and various influencing factors [16].
In this research, the elderly population was categorized into groups based on varying emotional states and sleep patterns to analyze discrepancies in HRV indicators among the eight groups. Findings revealed that individuals combined with anxiety, depression, and sleep disorders exhibited a decrease in all HRV metrics, with the exception of LF/HF, compared to the normal control group, with the most pronounced decrease observed in this cohort. Specifically, individuals with comorbid mood and sleep disturbances experienced a more substantial decline in HRV compared to those with singular anxiety, depression, or sleep disorders. This suggests that anxiety, depression, and sleep disorders may contribute to a reduction in HRV and exhibit a synergistic effect, a phenomenon not previously explored in existing literature. Consequently, our findings propose a novel hypothesis: a pronounced decrease in HRV may correlate with heightened emotional instability in patients and poorer sleep quality [17, 18].
Recent research has increasingly demonstrated the impact of mood disorders, such as anxiety and depression, on HRV. In particular, depressed mood has been associated with a heightened susceptibility to various cardiac ailments. While existing research has examined the correlation between depression and HRV, there remains a dearth of studies focusing on this relationship within the elderly demographic. This investigation utilized multivariate logistic regression analysis to investigate the distinct influence of anxiety and depression on HRV among elderly individuals. The findings revealed that anxiety independently posed a risk for the diminishment of SDNN, SDANN, and LF (P<0.05). This suggests that individuals with anxiety may experience a decrease in HRV measures, and that anxiety is an independent risk factor for an increase in the LF/HF ratio. The LF/HF ratio is commonly used as a marker of cardiovascular health, with an elevated ratio potentially indicating an autonomic nervous system imbalance. Similarly, depressive mood was found to be an independent risk factor for a reduction in SDNN, RMSSD, PNN50 and HF, suggesting that individuals with depression may experience decreased levels of these indicators due to the impact of their mood on balance of autonomic nervous system. Among them, RMSSD, PNN50, and HF have been identified as closely associated with parasympathetic nerve activity, suggesting that individuals with depression may exhibit diminished parasympathetic nerve activity. This finding supports the notion that depressive symptoms may exert an inhibitory influence on parasympathetic nerve activity, resulting in a reduction in HRV.
To sum up, the assessment of emotional disorders in the elderly population is significantly influenced by subjective factors inherent in the scales used, and various limitations, such as sensory impairments and cognitive dysfunction, may hinder the accurate measurement of these scales. Therefore, the utilization of HRV as an objective and easily accessible clinical monitoring indicator becomes imperative. By monitoring changes in SDNN, LF, and HF, healthcare professionals can effectively identify the presence and type of mood disorder in elderly patients.
Previous research has predominantly focused on examining the impact of various physiological and psychological factors on HRV. However, the prevalence of sleep disorders among the elderly poses a significant challenge to their overall physical and mental well-being, yet the potential influence of sleep disorders on HRV in this population remains largely unexplored. It is important to note that not only physical ailments, but also mental health conditions such as anxiety and depression, can contribute to the development of sleep disorders [19]. Hence, this study employed multivariate Logistic regression analysis to examine the potential influence of sleep disorders on HRV among elderly individuals. The results of the analysis indicated that sleep disorder emerged as a significant independent risk factor for the decline in PNN50 and SDANN. These findings align with some of the prior research, such as the study conducted by Trinder et al., which demonstrated a reduction in certain HRV measures, including RMSSD and PNN50, during nighttime in individuals with sleep disorders [20]. Moreover, Tobaldini et al. discovered a negative correlation between sleep disturbances and HRV in a cohort of young adults. Their findings indicated that individuals with insomnia exhibited notably decreased nighttime HRV, particularly in relation to parasympathetic parameters [21]. Another study utilized Actigraphy, a tool for evaluating sleep patterns, to investigate sleep quality and determined that diminished sleep efficiency was linked to reduced HRV [22]. This indicates that sleep disorders may result in dysfunction of specific autonomic nervous system functions, particularly those pertaining to cardiovascular well-being.
The limitation of this study is the lack of a clearly defined normal threshold for various HRV parameters in healthy individuals, despite the observed decrease in these parameters in individuals with anxiety, depression, and sleep disorders, particularly when all three conditions are present simultaneously. Future extensive clinical investigations are anticipated to establish a threshold level for HRV in the elderly demographic, thereby positioning HRV as a primary objective measure for assessing emotions.
Overall, HRV serves as a non-invasive and readily available tool for physicians to detect patients potentially impacted by negative mood and sleep disorders [23]. Investigating the correlation between anxiety, depression, sleep disorders, and HRV among older individuals will enhance comprehension of the psychological mechanisms underpinning associated illnesses and facilitate the formulation of potentially efficacious treatment strategies.