Cigarette smoking remains a major global public health challenge and is the foremost preventable cause of morbidity and mortality worldwide [1]. Its causal link to a wide array of diseases, particularly cardiovascular diseases (CVD) such as coronary artery disease, stroke, and peripheral vascular disease, is unequivocally established [2]. The pathophysiology linking smoking to CVD is multifactorial, involving endothelial dysfunction, inflammation, oxidative stress, and a prothrombotic state. A critical, yet often underappreciated, pathway is the profound impact of smoking on the autonomic nervous system (ANS) [3].

The ANS is a vital regulator of cardiovascular homeostasis, modulating heart rate, blood pressure, and myocardial contractility through a delicate balance between its sympathetic and parasympathetic branches. Sympathetic activation prepares the body for "fight-or-flight" responses, increasing heart rate and vasoconstriction, while the parasympathetic (vagal) system promotes "rest-and-digest" functions, primarily by slowing the heart rate. A chronic shift in this balance towards sympathetic predominance and/or parasympathetic withdrawal is a well-recognized contributor to arrhythmogenesis, hypertension, and overall cardiovascular risk [4].

Heart rate variability (HRV) has emerged as a powerful, non-invasive, and quantitative tool for assessing cardiac autonomic control [5]. By analyzing the variations in the interval between successive R-waves (NN intervals) on an electrocardiogram, HRV provides distinct metrics that reflect the modulatory inputs of the ANS on the sinoatrial node. Time-domain indices, such as the standard deviation of all NN intervals (SDNN) and the root mean square of successive differences between normal heartbeats (RMSSD), reflect overall variability and vagal tone, respectively. Frequency-domain analysis partitions the total variance into its frequency components, primarily low-frequency (LF; 0.04–0.15 Hz) and high-frequency (HF; 0.15–0.4 Hz) power. HF power is widely accepted as a marker of parasympathetic (vagal) modulation, whereas the LF component is influenced by both sympathetic and parasympathetic activity. The ratio of LF to HF power (LF/HF) is often used as an index of sympathovagal balance [6].

Several studies have investigated the relationship between smoking and HRV. Acute exposure to nicotine, the primary psychoactive component of tobacco, is known to induce a transient increase in heart rate and blood pressure, consistent with sympathetic activation [7]. Studies on chronic smoking have consistently reported altered HRV parameters. For instance, Barutcu et al. demonstrated significantly lower time- and frequency-domain HRV values in long-term smokers compared to controls, suggesting a state of cardiac autonomic dysregulation [8]. Similarly, a meta-analysis confirmed that smokers generally exhibit lower HRV, particularly a reduction in indices of vagal control [9].

Despite this established link, there remains a need for well-controlled studies to further characterize these autonomic alterations. Many earlier studies were limited by small sample sizes, inadequate control for confounders such as age and physical activity, or variability in HRV recording protocols. A deeper understanding of the specific pattern of autonomic dysfunction—whether it is primarily due to sympathetic overactivity, parasympathetic withdrawal, or both—is crucial for elucidating the mechanisms of smoking-related cardiovascular risk and for developing targeted interventions.

Therefore, the aim of this study was to comprehensively assess cardiac autonomic function by comparing a full spectrum of time- and frequency-domain HRV parameters between a well-defined cohort of chronic smokers and an age- and sex-matched group of healthy non-smoking controls. We hypothesized that chronic smokers would exhibit significantly reduced HRV, reflecting a shift in sympathovagal balance towards sympathetic predominance.

Study Design and Participants

A total of 100 participants were recruited from the local community through advertisements and outpatient clinics. Participants were allocated into two groups: a smoker group (n=50) and a non-smoker control group (n=50).

Inclusion and Exclusion Criteria

Inclusion criteria for the smoker group were: (1) age between 25 and 50 years; (2) a history of smoking 10 or more cigarettes per day for at least 5 consecutive years; and (3) currently smoking. For the non-smoker group, participants were age- and sex-matched individuals who had never smoked.

General exclusion criteria for all participants included: (1) history of known cardiovascular diseases (e.g., hypertension, coronary artery disease, heart failure, significant arrhythmia); (2) diabetes mellitus or other endocrine disorders; (3) neurological or psychiatric conditions; (4) chronic respiratory diseases other than smoking-related symptoms; (5) morbid obesity (Body Mass Index [BMI] > 35 kg/m²); and (6) use of any medication known to affect autonomic nervous system function (e.g., beta-blockers, anti-depressants, anti-cholinergics).

Procedures

Participants were instructed to abstain from caffeine, alcohol, and strenuous exercise for 24 hours prior to their scheduled visit. Smokers were asked to refrain from smoking for at least 2 hours before the recording to minimize the acute effects of nicotine.

Upon arrival at the laboratory, participants underwent a screening process to confirm eligibility. A detailed questionnaire was administered to collect data on demographics, medical history, lifestyle factors, and smoking habits (cigarettes per day, duration of smoking). Pack-years were calculated as (cigarettes per day / 20) × years of smoking. Anthropometric measurements, including height and weight, were taken to calculate BMI.

Following the initial assessment, participants rested in a supine position for 15 minutes in a quiet, temperature-controlled room (22–24°C). A standard 3-lead electrocardiogram (ECG) was connected, and a continuous 5-minute Lead-II ECG signal was recorded using a PowerLab 4/35 data acquisition system (ADInstruments, Dunedin, New Zealand) with a sampling rate of 1000 Hz. Participants were instructed to remain still and breathe normally during the recording.

Heart Rate Variability Analysis

The recorded ECG data were exported for offline analysis. R-R intervals (NN intervals) were automatically detected, and the time series was manually inspected for artifacts and ectopic beats, which were corrected using an interpolation method. Only recordings with >95% normal sinus beats were included in the final analysis.

• HRV analysis was performed using the Kubios HRV Standard software (version 3.5, Kubios Oy, Kuopio, Finland).

Statistical Analysis

All statistical analyses were performed using SPSS for Windows, version 25.0 (IBM Corp., Armonk, NY). Data were tested for normality using the Shapiro-Wilk test. Continuous variables are presented as mean ± standard deviation (SD). Categorical variables are presented as frequencies and percentages (%). An independent samples t-test was used to compare continuous variables (demographics and HRV parameters) between the smoker and non-smoker groups. A Chi-square test was used for the comparison of categorical variables (sex). A p-value of < 0.05 was considered statistically significant for all tests.

A total of 100 participants completed the study, with 50 in the smoker group and 50 in the non-smoker group. The baseline demographic and clinical characteristics of the study population are presented in Table 1.

The two groups were successfully matched for age, sex, and Body Mass Index (BMI), with no statistically significant differences observed (p > 0.05 for all). In the smoker group, the average number of cigarettes smoked per day was 18.4 ± 5.1, and the mean smoking duration was 14.6 ± 5.9 years, resulting in an average pack-year history of 13.5 ± 5.3.

Table 1. Demographic and Clinical Characteristics of Study Participants

Time-Domain HRV Parameters

The comparison of time-domain HRV parameters is shown in Table 2. The smoker group exhibited significantly lower values for both SDNN and RMSSD compared to the non-smoker group. The mean SDNN was 23.7% lower in smokers (42.1 ± 10.5 ms vs. 55.2 ± 12.1 ms, p<0.001), indicating reduced overall heart rate variability. The mean RMSSD, a specific marker of vagal tone, was 34.3% lower in smokers (25.3 ± 8.1 ms vs. 38.5 ± 9.8 ms, p<0.001).

Table 2. Comparison of Time-Domain HRV Parameters between Smokers and Non-smokers

Frequency-Domain HRV Parameters

The results of the frequency-domain analysis are detailed in Table 3. Smokers demonstrated a marked reduction in parasympathetic activity, as evidenced by significantly lower absolute HF power compared to non-smokers (320 ± 110 ms² vs. 550 ± 150 ms², p<0.001). While there was no statistically significant difference in absolute LF power between the groups (p=0.210), the LF/HF ratio was significantly higher in the smoker group (2.8 ± 0.9 vs. 1.5 ± 0.5, p<0.001). This indicates a substantial shift in the sympathovagal balance towards sympathetic predominance.

Table 3. Comparison of Frequency-Domain HRV Parameters between Smokers and Non-smokers

The principal finding of this study is that chronic cigarette smokers exhibit significant cardiac autonomic dysfunction compared to age- and sex-matched non-smokers. This dysfunction is characterized by a marked reduction in overall HRV, a significant withdrawal of parasympathetic (vagal) activity, and a resultant shift in sympathovagal balance towards sympathetic dominance. These results provide robust evidence for the deleterious subclinical effects of long-term smoking on cardiovascular regulation.

Our findings of decreased time-domain parameters in smokers align with a large body of existing literature. The reduction in SDNN observed in our smoking cohort suggests a blunting of the overall adaptive capacity of the heart to respond to physiological and environmental stimuli [5]. More specifically, the profound decrease in RMSSD, a highly specific marker of vagal influence on the heart, points to parasympathetic withdrawal as a key feature of the autonomic profile in smokers. This is clinically significant, as reduced vagal tone is a powerful predictor of ventricular arrhythmias and sudden cardiac death [10].

The frequency-domain results further elucidate the nature of this autonomic imbalance. The significantly lower HF power in smokers directly corroborates the RMSSD finding, confirming a substantial impairment in cardiac parasympathetic modulation. The HF component of HRV is generated by respiratory sinus arrhythmia and is mediated purely by the vagus nerve; its suppression is a hallmark of cardiovascular risk [6]. Interestingly, we did not find a significant difference in absolute LF power between the two groups. While LF power is often considered a marker of sympathetic activity, it is now understood to be influenced by both sympathetic and parasympathetic inputs, as well as baroreflex activity [11]. The lack of change in LF power, coupled with a drastic reduction in HF power, led to a markedly elevated LF/HF ratio in smokers. This elevated ratio strongly suggests that the autonomic imbalance in chronic smokers is driven primarily by vagal withdrawal rather than a direct, sustained increase in sympathetic outflow, at least in a resting state.

The pathophysiological mechanisms underlying these observations are likely multifactorial. Nicotine is a potent sympathomimetic agent that acutely increases catecholamine release by stimulating nicotinic acetylcholine receptors in the adrenal medulla and sympathetic ganglia [7]. While our study protocol minimized these acute effects, chronic exposure to nicotine and thousands of other toxins in cigarette smoke can lead to long-term neuroplastic changes. These include central desensitization of baroreflex pathways and peripheral neuronal damage [3]. Furthermore, chronic systemic inflammation and oxidative stress, well-documented consequences of smoking, can directly impair vagal function and promote a pro-sympathetic state [12].

The clinical implications of our findings are substantial. Depressed HRV is an established independent risk factor for adverse cardiovascular events, including myocardial infarction and all-cause mortality, in both healthy populations and patients with existing CVD [13]. Our study demonstrates that smokers, even those without clinically apparent disease, harbor a high-risk autonomic profile. This subclinical autonomic dysfunction likely represents a crucial intermediate step in the pathway from smoking to overt cardiovascular disease. Therefore, HRV analysis could serve as a valuable tool in clinical practice to demonstrate the tangible, albeit silent, physiological damage caused by smoking, potentially enhancing motivation for smoking cessation.

This study has several strengths, including a well-characterized cohort, rigorous matching of control subjects to minimize confounding by age and sex, and a standardized, laboratory-based protocol for HRV recording and analysis. However, some limitations must be acknowledged. First, the cross-sectional design precludes any inference of causality. Second, we relied on self-reported smoking status and did not biochemically verify it with measures like serum cotinine. Third, we only assessed short-term HRV from a 5-minute recording, which may not capture the full range of autonomic function, such as circadian variations that can be assessed with 24-hour monitoring. Future research should employ longitudinal designs to track changes in HRV following smoking cessation and should explore the dose-response relationship between smoking intensity/duration and the degree of autonomic dysfunction.

In conclusion, this study demonstrates that chronic cigarette smoking is associated with significant and multifaceted cardiac autonomic dysfunction. Smokers exhibit a clear pattern of reduced overall heart rate variability, characterized predominantly by a profound withdrawal of parasympathetic nervous activity. This leads to a state of relative sympathetic dominance, a well-known precursor to adverse cardiovascular events. These findings highlight HRV analysis as a sensitive marker for detecting the subclinical cardiovascular harm induced by smoking and reinforce the critical importance of smoking cessation as a primary strategy for cardiovascular disease prevention.

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