Association of heart rate variability index with depressive symptoms and lung function in chronic obstructive pulmonary disease

Abstract

BACKGROUND

Depression is a common comorbidity in patients with chronic obstructive pulmonary disease (COPD). Research indicates that COPD affects cardiac autonomic control, and heart rate variability (HRV) serves as a simple, non-invasive measure of autonomic nerve activity. However, the relationship between HRV and lung function, as well as the impact of depressive symptoms, remains unclear.

AIM

To investigate the correlation between HRV indicators and depressive symptoms and lung function in patients with COPD.

METHODS

A retrospective cross-sectional study involving 120 COPD patients hospitalized from January 2018 to January 2024 at our institution was conducted. Demographic and clinical characteristics were collected, and depressive symptoms were assessed using the Beck Depression Inventory (BDI). Patients were categorized into a depressed group (BDI ≥ 16) and a non-depressed group (BDI < 16). A control group consisting of 60 healthy volunteers who underwent check-ups at the same institution was also included. Statistical analyses were performed using SPSS 26.0 software. Pearson correlation coefficients were calculated to determine and compare the relationships between HRV parameters, lung function measures, and depressive symptoms across the groups.

RESULTS

Of the 120 patients with COPD, 35.8% (43/120) were diagnosed with depression, compared to 5.0% (3/60) in the control group. The HRV index in COPD patients was significantly lower than that in the control group (P < 0.05), and the value in the depressed group was significantly lower than that in the non-depressed group (P < 0.05). Similarly, the COPD group had a significantly lower pulmonary forced vital capacity (FVC), first-second expiratory volume (FEV1) and FEV1/FVC ratios than the control group (P < 0.05), and the depressed group was significantly lower than that in the non-depressed group (P < 0.05). Pearson correlation analysis revealed that the standard deviation of normal R-R intervals, standard deviation of the mean of 5-minute normal R-R intervals, root mean square of successive differences of normal R-R intervals, percentage of normal R-R intervals greater than 50 ms, high-frequency, and low-frequency indices showed positive correlations with lung function parameters (P < 0.05) and negative correlations with BDI scores (P < 0.05).

CONCLUSION

Compared to patients without COPD, the incidence of depressive symptoms is higher among patients with COPD and is negatively correlated with the patients’ HRV indices. In contrast, HRV indices are positively correlated with the patients’ pulmonary function parameters. Patients and healthcare professionals should enhance their awareness of depression, actively conduct depression assessment screenings, and incorporate HRV indices into disease management. This approach aims to improve the psychological health of patients and ultimately enhance their prognosis and quality of life.

Key Words: Chronic obstructive pulmonary disease; Heart rate variability; Lung function; Depression; Beck depression inventory

Core Tip: Among 120 chronic obstructive pulmonary disease (COPD) patients, 35.8% (43/120) suffered from depression, compared to 5.0% (3/60) in the control group. Heart rate variability (HRV) indices, such as standard deviation of normal R-R intervals, standard deviation of the mean of 5-minute normal R-R intervals, root mean square of successive differences of normal R-R intervals, percentage of normal R-R intervals greater than 50 ms, high-frequency, and low-frequency were significantly lower in both depressed and non-depressed groups of COPD patients compared to controls (P < 0.05). Forced vital capacity (FVC), first-second expiratory volume (FEV1), and FEV1/FVC ratios were also significantly lower in both COPD patient groups compared to controls (P < 0.05). Pearson correlation analysis indicated positive correlations between HRV indices and lung function measures (P < 0.05) and negative correlations with Beck Depression Inventory scores (P < 0.05).

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is a systemic inflammatory disease primarily characterized by pulmonary symptoms[1]. It is primarily caused by exposure to a significant amount of harmful gases or toxic particles, such as tobacco smoke and 2.5-micrometer particulate matter, which leads to airway and alveolar damage and subsequent persistent and irreversible airflow limitation. COPD is one of the four major causes of mortality worldwide, along with ischemic heart disease, cerebrovascular diseases, and cancer, and its prevention and management impose a substantial economic burden on families and national health insurance systems[2]. Currently, the direct medical costs associated with COPD in China range from 72 dollars to 3565 dollars per person per year, accounting for 33.33% to 118.09% of the local annual income. This places COPD among the top three diseases in terms of economic burden[3]. Recent epidemiological surveys indicate that the overall prevalence of COPD in China is 8.6%, equating to approximately 99 million affected individuals, with a prevalence rate of 13.7% among those aged 40 and older[4]. COPD is characterized by chronic respiratory symptoms such as cough, sputum production, wheezing, and dyspnea, all of which progressively worsen with age and declining lung function, subsequently impacting daily activities and quality of life[5]. As the degree of airway obstruction intensifies and oxygen demand increases, patients often find their routine activities increasingly limited, frequently requiring long-term care from family members or hired caregivers, which further exacerbates the family burden. COPD commonly coexists with one or more additional diseases of varying severity, including cardiovascular diseases, diabetes, neurological and psychiatric disorders, musculoskeletal diseases, and lung cancer. The management of comorbidities is a crucial determinant of prognosis[6]. In recent years, the focus of COPD treatment has shifted from merely delaying the decline in lung function and reducing mortality rates to a patient-centered approach aimed at improving daily function and health status, as well as addressing relevant comorbidities. This trend is reflected in increased assessments of patients’ quality of life, anxiety and depression status, and treatment strategies[7].

Depression is a common comorbidity in patients with COPD[8,9]. Due to the overlap between the clinical manifestations of depression and the physical and psychological symptoms seen in COPD patients, the diagnostic process can become complex. The prevalence of psychiatric comorbidities among these patients and the effectiveness of treatment and prognosis remain unclear. A meta-analysis of 39587 COPD patients and 39431 controls conducted in 2011 found that the probability of experiencing depressive symptoms in COPD patients was 24.6% [95% confidence interval (CI): 20.0-28.6], which was significantly higher than the control group’s 11.7% (95%CI: 9.0-15.1)[10]. Additionally, a study in China of 1100 patients found that 35.7% of outpatients with COPD suffered from depression[11]. A survey conducted in the Pudong district of Shanghai found a depression incidence rate of 13.4% among 275 patients with mild to moderate COPD[12]. The Beck Depression Inventory (BDI) is one of the most widely used self-report assessment tools for evaluating depression and is easily accessible, making it a common choice in clinical practice[13]. Therefore, we utilized the BDI in this study to assess depressive symptoms in patients.

Heart rate variability (HRV) refers to the small fluctuations observed in the R-R intervals of an electrocardiogram (ECG) during heartbeats[14]. Analyzing and processing these minor fluctuations through ECG can provide insights into the cardiovascular and nervous systems relating to HRV. HRV serves as a non-invasive indicator of autonomic nervous activity, where changes in heart rate can be influenced by both sympathetic and parasympathetic nervous system activity. Increased sympathetic nervous system stimulation can lead to elevated heart rates, whereas parasympathetic nervous system activation can cause decreases in heart rate. In general, heart rate and rhythm are largely regulated by the autonomic nervous system[15].

Literature indicates that COPD patients may experience abnormalities in HRV due to the impacts of their underlying condition on autonomic nervous function[16,17]. Common HRV indices include the standard deviation of normal R-R intervals (SDNN), the standard deviation of the mean of 5-minute normal R-R intervals (SDANN), the root mean square of successive differences of normal R-R intervals (rMSSD), the percentage of normal R-R intervals greater than 50 ms (PNN50), and high-frequency (HF) and low-frequency (LF) values[18]. There is relatively limited research on the relationship between HRV indices and lung function or depressive symptoms in COPD patients. For instance, studies have found that HRV indices in COPD patients are significantly lower than those in healthy control groups, which may be related to autonomic nervous system dysfunction[19]. Additionally, depression is more prevalent among COPD patients and is closely associated with their quality of life[20]. Therefore, understanding the relationship between HRV, lung function, and depressive symptoms in COPD is crucial for improving the overall health status of patients.

In summary, the purpose of this study was to analyze the correlation between HRV index and lung function and the influence of depressive symptoms in COPD patients, with a goal of providing data support for the prevention and treatment of heart disease and depression in COPD patients.

MATERIALS AND METHODS

General information

This is a retrospective cross-sectional study in which we identified COPD patients using information retrieved from referral records, physical examination results, medication and treatment orders, and discharge documents. We collected data from a total of 60 healthy control participants with no underlying lung diseases or respiratory symptoms and 120 patients with COPD who were seen in our hospital’s Pulmonology department. According to Oh and Cloninger[21], a BDI threshold of 16 was used to differentiate between patients with mild or no depression (BDI < 16) and those with moderate to severe depression (BDI ≥ 16).

In this study, COPD patients with a BDI score ≥ 16 were classified into the depressive symptom group (n = 43), while those with a BDI score < 16 were classified into the non-depressive symptom group (n = 77). This research was conducted in accordance with the Declaration of Helsinki and received approval from the hospital’s ethics committee, with all patients providing written informed consent.

Inclusion criteria: COPD was diagnosed in accordance with the Global Initiative for Chronic Obstructive Lung Disease recommendations[22]. The criteria specified that the ratio of forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) (FEV1/FVC) must be < 70%, and FEV1 must be < 80% of the predicted value (FEV1% pred).

Exclusion criteria: (1) Patients with bronchial asthma; (2) Bronchiectasis; (3) Pulmonary tuberculosis; (4) Diffuse panbronchiolitis; (5) Obliterative bronchiolitis and/or (6) Interstitial lung disease; (7) Patients who had undergone lung surgery within the past 6 months; (8) Individuals with a new onset of tumors in the past 5 years or with a history of tumors, regardless of treatment, recurrence, or metastasis; (9) Missing HRV indices; (10) Patients without a BDI depression score; and (11) Those with incomplete clinical data.

A total of 360 COPD patients were screened for inclusion. Among these, 73 patients had incomplete pulmonary function data, 98 patients’ records lacked relevant BDI assessments, and 69 patients had missing HRV indices. Ultimately, 120 patients (33.3%) were included in the analysis.

Sample size calculation

Sample size was calculated according to the following formula: N = Z² × P (1-P)/d² = 114, where N is the sample size, Z is the statistic corresponding to the 95%: 1.96, P is the estimated prevalence of COPD in the general population = 5%, and d is the accuracy rate = 0.04.

Measurement methods

Measurement of HRV indices: COPD patients underwent examinations before treatment, while control group participants were assessed on the same day as their physical examinations. During the measurement period, participants engaged in normal activities, maintaining steady breathing and relaxation. To ensure data accuracy and completeness, patients were advised to avoid strenuous activities, excessive caffeine, and alcohol during the 24-hour Holter ECG measurement. The Holter monitor was closely fitted to minimize movement artifacts. The 24-hour Holter ECG was used to measure HRV indices, with the LF domain was set to 0.04-0.15 Hz and the HF domain was set to 0.16-0.40 Hz. The following HRV indices were measured: SDNN, SDANN, rMSSD, PNN50, HF value and LF value.

Pulmonary function assessment

Pulmonary function was measured using the American Pulmonary Function Analyzer (VMAX2130; Sensor Medics Corporation, Yorba, CA, United States). The subjects’ lung function was assessed while in a resting state, and patients were instructed to assume a relaxed seated position and maintain steady breathing during the measurement. The primary parameters measured included: FVC, FEV1, and the ratio of FEV1 to FVC (FEV1/FVC).

Depression assessment tool

The presence of depression was defined by the total BDI score. The BDI is one of the most widely used tools for assessing depression, and it evaluates the patient’s emotional, cognitive, motivational, and physiological states. It consists of 21 self-reported items, with scores ranging from 0 to 63; higher scores indicate greater depression severity. The assessment typically takes 5-10 minutes to complete and has been extensively used to screen for depression in COPD patients. Based on prior research, patients with a BDI score of ≥ 16 were classified as having depressive symptoms.

Data collection

In addition to collecting the aforementioned HRV indices (SDNN, SDANN, rMSSD, PNN50, HF, LF), pulmonary function parameters (FVC, FEV1, FEV1/FVC), and BDI scores, other baseline-related information was gathered. These data included age, gender, marital status, education level, socioeconomic status, occupational activity, smoking status, respiratory medication treatment, long-term oxygen therapy, and dyspnea (assessed using the modified medical research council scale). Furthermore, pulmonary function was evaluated through FVC measurements and bronchodilator tests, static lung volumes measured via whole-body plethysmography, diffusion capacity for carbon monoxide, and arterial blood gas analysis. Additionally, a 6-minute walk test was conducted.

Outcome measures

The following comparisons were made: Comparison of pulmonary function parameters among the three groups, including FVC, FEV1, and FEV1/FVC. Comparison of HRV indices among the three groups, including SDNN, SDANN, rMSSD, PNN50, HF, and LF. Comparison of BDI scores among the three groups. Utilization of Pearson correlation analysis to assess the relationship between HRV indices (SDNN, SDANN, rMSSD, PNN50, HF, LF) and pulmonary function parameters (FVC, FEV1, FEV1/FVC) as well as depressive symptoms (BDI scores) in patients with COPD.

Statistical analysis

Results are expressed as mean ± SD for variables that follow a normal distribution and as median interquartile range for those that do not. Frequencies and percentages are used to report categorical variables. The normality of continuous variables was evaluated using the Kolmogorov-Smirnov test. Categorical data were examined using Pearson’s χ² test or Fisher’s exact test. Multi-group comparisons were performed using one-way analysis of variance and expressed as F. The association between numerical variables was assessed using either Pearson or Spearman’s rho correlation. Multivariate linear regression analysis was performed to determine the independent factors related to mean HRV. Two-sided P values were calculated, with significance set at P < 0.05. All analyses were conducted using SPSS software (version 26.0, SPSS Inc., Chicago, IL, United States).

RESULTS

Comparison of baseline data results

In the control group, 5.0% of patients (3/60) suffered from depression. In the COPD group, the overall prevalence of depression was 35.8% (43/120 participants) and the mean BDI score was 8.2. Most patients (91.67%) were male, and the median age was 67.7 (61.2-73.8) years. A total of 80% of patients were married. Other clinical baseline features are shown in Table 1.

Table 1 Socio-demographic and clinical characteristics of 120 patients with chronic obstructive pulmonary disease, mean ± SD.

	Patient (n = 120)	Percentage (%)
BDI score		8.2 ± 6.5
Depression	43.00	35.80
Males	110	91.67
Age (years), median (P25-P75)	67.7 (61.2-73.8)
Married	96	80.00
Less than primary education	49	40.83
Low socioeconomic status (IV-V)	97	80.83
Current workers	19	15.83
Smoking status
Current smoker	39	32.50
Former smoker	80	66.67
Never smoked	1	0.83
MMRC dyspnea scale, median (P25-P75)	2 (2-3)
Hemoglobin, g/dL	14.5 ± 1.4
Albumin, g/dL	4.2 ± 0.5
Diffusing capacity for carbon monoxide	65.1 ± 18.3
PaO2 (mmHg)	73.5 ± 10.4
PaCO2 (mmHg)	52.6 ± 17.3

BDI: Beck depression inventory; MMRC: Modified medical research council; PaO₂: Partial pressure of oxygen in arterial blood; PaCO₂: Partial pressure of carbon dioxide in arterial blood.

Comparison of depressive symptoms and pulmonary function indicators in each group

The indexes of FVC, FEV1 and FEV1/FVC in COPD patients with or without depression were lower than those in the control group (P < 0.05). The pulmonary function indices of patients with depression were significantly lower than those of patients without depression (P < 0.05). The BDI scores of COPD patients in both the depression group and the non-depression group were higher than those in the control group (P < 0.05). The BDI score of patients with depression was significantly higher than that of patients without depression (P < 0.05). See Table 2.

Table 2 Comparison of depressive symptoms and pulmonary function indicators in each group, mean ± SD.

Variable	Without depression (n = 77)	Depression (n = 43)	Control (n = 60)	P value
BDI score	5.7 ± 4.3	21.8 ± 5.9	2.6 ± 1.5	< 0.001
Lung function
FEV1 (L)	2.86 ± 0.67	2.06 ± 0.43	3.65 ± 0.78	< 0.001
FVC (L)	2.90 ± 0.72	1.43 ± 0.82	3.46 ± 0.57	< 0.001
FEV1/FVC	72.1 ± 6.03	58.2 ± 6.73	88.2 ± 8.76	< 0.001

BDI: Beck depression inventory; FEV1: First-second expiratory volume; FVC: Forced vital capacity.

Comparison of relevant HRV indices in each group

The HRV indexes SDNN, SDANN, rMSSD, PNN50, HF and LF in COPD patients without depression and with depression were lower than those in the control group (all P < 0.05). The HRV in the depression group was significantly lower than that in non-depression group (P < 0.05). See Table 3.

Table 3 Comparison of relevant indexes of heart rate variability of subjects in each group, mean ± SD.

Variable	Without depression (n = 77)	Depression (n = 43)	Control (n = 60)	P value
SDNN (ms)	108.32 ± 17.68	83.21 ± 14.26	148.27 ± 34.73	< 0.001
SDANN (ms)	101.17 ± 13.82	84.54 ± 11.24	136.38 ± 24.12	< 0.001
rMSSD (ms)	32.47 ± 10.23	23.62 ± 8.21	42.72 ± 11.24	< 0.001
PNN50 (%)	13.68 ± 4.91	7.41 ± 2.03	23.85 ± 7.43	< 0.001
HF (ms)	2689.21 ± 841.38	1037.64 ± 302.54	6983.62 ± 1096.37	< 0.001
LF (ms)	963.81 ± 164.82	547.92 ± 110.04	1182.73 ± 287.41	< 0.001

SDNN: Standard deviation of normal-to-normal intervals; SDANN: Standard deviation of the average of normal-to-normal intervals; rMSSD: Root mean square of successive differences of normal-to-normal intervals; PNN50: Percent of pairs of successive normal intervals that differ by more than 50 ms; HF: High frequency; LF: Low frequency.

Correlation of heart rate variation index with BDI and pulmonary function index

We performed Pearson correlation analysis and found that as HRV indices such as SDNN, SDANN, r-MSSD, pNN50, HF and LF increased in COPD patients, BDI scores decreased and indicators of lung function (FVC, FEV and FVC/FEV) increased. HRV was negatively correlated with BDI scores in COPD patients but positively correlated with lung function (P < 0.05). See Table 4.

Table 4 Correlation between heart rate variability, Beck Depression Inventory score and lung function in chronic obstructive pulmonary disease patients.

HRV		SDNN (ms)	SDANN (ms)	rMSSD (ms)	PNN50 (%)	HF (ms)	LF (ms)
BDI	r value	-0.673	-0.712	-0.706	-0.731	-0.632	-0.613
	P value	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001
FVC	r value	0.743	0.772	0.692	0.713	0.791	0.732
	P value	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001
FEV1	r value	0.782	0.731	0.785	0.698	0.801	0.763
	P value	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001
FEV1/FVC	r value	0.719	0.692	0.783	0.772	0.795	0.697
	P value	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001	< 0.001

SDNN: Standard deviation of normal-to-normal intervals; SDANN: Standard deviation of the average of normal-to-normal intervals; rMSSD: Root mean square of successive differences of normal-to-normal intervals; PNN50: Percent of pairs of successive normal intervals that are differing by more than 50 ms; HF: High frequency; LF: Low frequency; HRV: Heart rate variability; FEV1: First-second expiratory volume; FVC: Forced vital capacity.

DISCUSSION

One cohort study showed that patients diagnosed with COPD were 42% more likely to develop depression than non-COPD patients, and patients with more severe dyspnea were at greater risk of depression[9]. Another study showed that the prevalence of depression in COPD patients ranged from 6.7% to 58%[23]. In this study, we aimed to investigate the relationship between HRV indices, depressive symptoms, and pulmonary function parameters in patients with COPD. Our findings demonstrate that both depressive symptoms and pulmonary function indicators are significantly impaired in COPD patients compared to healthy controls. In this study, we used BDI scale to assess the depressive status of 120 COPD patients and found that depression accounted for 35.8% (43/120) of COPD patients, corroborating existing literature on the prevalence of depression in this population.

We observed that the FVC, FEV1, and the FEV1/FVC ratio in both the depression and non-depression groups of COPD patients were significantly lower than those in the control group (P < 0.05). Moreover, patients with depression exhibited notably poorer pulmonary function than their non-depressed counterparts (P < 0.05). These results align with previous studies indicating that depressive symptoms adversely affect lung function[24], potentially due to both physiological and behavioral factors. The study by O’Toole et al[25] showed that depression is more strongly associated with many patient reported outcomes at baseline and their change over time compared with FEV1%. Recognizing and incorporating the impact of depressive symptoms into individualized care may improve COPD outcomes.

In terms of depressive symptoms, the BDI scores for both groups of COPD patients were significantly higher than those of the control group (P < 0.05), and the scores for the depression group surpassed those of the non-depression group (P < 0.05). This underscores the high prevalence of depression among COPD patients and suggests that depressive symptoms could exacerbate disease severity[26]. For instance, a study by Weiss et al[27] also found a significant correlation between depressive symptoms in COPD patients and disease severity, which aligns with our results and suggests that depression may play an important role in COPD pathophysiology.

Furthermore, HRV is a quantitative index reflecting the activity of the body’s autonomic nervous system, which is an important system affecting cardiac bioelectrophysiology[28]. The interaction between the sympathetic nerve and the vagus nervous system results in irregular heart rate changes. Under physiological conditions, the activities of the sympathetic nerve and the vagus nerve show a balanced state. However, certain pathological conditions can cause the balance between the two to be broken, resulting in changes in HRV[29]. Current studies suggest that changes in HRV reflect the decrease of ventricular fibrillation threshold and the increase in the incidence of arrhythmias, which are prone to tachycardia, ventricular fibrillation and sudden death. Therefore, HRV is also used as an indicator to predict arrhythmias and sudden death. In the time domain index of HRV, the SDNN value primarily reflects the total sympathetic nerve and vagus nerve tension, SDANN mainly reflects sympathetic nerve tension, and rMSDNN and pNN50 reflect vagus nerve tonation[30]. Our analysis of HRV revealed that indices such as SDNN, SDANN, r-MSSD, PNN50, HF, and LF components were significantly reduced in both the depressed and non-depressed COPD groups compared to controls (all P < 0.05). Notably, the depressed group showed significantly lower HRV indices compared to the non-depressed group (P < 0.05). These findings are consistent with previous research indicating that decreased HRV is associated with increased depressive symptoms and poorer health outcomes.

Our Pearson correlation analysis further elucidated the relationship between HRV indices and clinical parameters. We found that higher values of SDNN, SDANN, r-MSSD, PNN50, HF, and LF were associated with lower BDI scores and higher pulmonary function metrics (FVC, FEV1, and FEV1/FVC). This indicates a negative correlation between HRV and depressive symptoms, alongside a positive correlation between HRV and pulmonary function parameters (P < 0.05). This pattern suggests that improved HRV might be indicative of better mood and higher pulmonary function in COPD patients[31].

The underlying mechanisms linking HRV, depression, and lung function may involve autonomic nervous system dysregulation, inflammatory processes, and social behavioral modifications. It is essential to consider these interrelationships in treatment strategies for COPD patients, highlighting the need for integrated care approaches that address both psychological and physical health. Early identification of depression can facilitate timely interventions, such as counseling or cognitive-behavioral therapy, which may enhance patients’ mood and potentially improve their lung function and HRV. Additionally, incorporating lifestyle modifications that promote physical activity and relaxation techniques, such as yoga or mindfulness, could help improve HRV and overall well-being.

To conclude, our results highlight the complex interplay between HRV, depressive symptoms, and pulmonary function in COPD patients. These findings suggest that enhancing HRV could be beneficial for improving mood and lung function, thus emphasizing the importance of routine screening for depression in this population. Future studies should investigate the causal relationships and potential interventions targeting both psychological and physiological aspects of COPD to improve overall patient outcomes. By demonstrating the clinical relevance of HRV and its relationship with depression and lung function, our research could lay the groundwork for more personalized treatment strategies in COPD management.

CONCLUSION

In summary, compared with patients without COPD, the incidence of depressive symptoms is higher among patients with COPD and is negatively correlated with the patients’ HRV indices. In contrast, HRV indices are positively correlated with the patients’ pulmonary function parameters. Healthcare professionals, as well as the patients themselves, should enhance their awareness of depression, actively conduct depression assessment screenings, and incorporate HRV indices into disease management. This approach aims to improve the psychological health of patients and ultimately enhance their prognosis and quality of life.