CONTEXT: Though many studies have been conducted on the effect of chronic smoking on pulmonary function test (PFT) and heart rate variability (HRV), no study has found a correlation between the pulmonary function test and heart rate variability parameters so far. AIM: The aim was to study if there was a correlation, if any, between PFT and HRV. SETTINGS AND DESIGN: Thirty male subjects who were chronic smokers of at least 10 pack years and another 30 nonsmoking healthy males were included in the study and were matched for age, height, weight, and body surface area. MATERIALS AND METHODS: PFT and HRV were performed on these subjects and a correlation was statistically derived. STATISTICAL ANALYSIS USED: Spearman's correlation coefficient was used for the analysis of HRV and PFT. Multiple stepwise regression analysis was used subsequently. RESULTS: HF and LF showed correlation coefficients of 0.378 and-0.383 with forced expiratory volume in the first second (FEV 1) and peak expiratory flow rate (PEFR), respectively. It was found that only FEV 1/FVC was having a statistically significant regression coefficient with HF the R-value was found to be 0.425 while with other parameters, it was not significant. CONCLUSION: We conclude that smoking affects all the parameters of PFT and HRV. Since there is a correlation between PFT parameters (PEFR and FEV1) and HRV parameter (LF and HF), this can help us in predicting cardiac morbidity in chronic smokers. So HRV should be included as a routine test along with PFT in chronic smokers for early diagnosis of cardiac involvement.
CONTEXT: Though many studies have been conducted on the effect of chronic smoking on pulmonary function test (PFT) and heart rate variability (HRV), no study has found a correlation between the pulmonary function test and heart rate variability parameters so far. AIM: The aim was to study if there was a correlation, if any, between PFT and HRV. SETTINGS AND DESIGN: Thirty male subjects who were chronic smokers of at least 10 pack years and another 30 nonsmoking healthy males were included in the study and were matched for age, height, weight, and body surface area. MATERIALS AND METHODS: PFT and HRV were performed on these subjects and a correlation was statistically derived. STATISTICAL ANALYSIS USED: Spearman's correlation coefficient was used for the analysis of HRV and PFT. Multiple stepwise regression analysis was used subsequently. RESULTS: HF and LF showed correlation coefficients of 0.378 and-0.383 with forced expiratory volume in the first second (FEV 1) and peak expiratory flow rate (PEFR), respectively. It was found that only FEV 1/FVC was having a statistically significant regression coefficient with HF the R-value was found to be 0.425 while with other parameters, it was not significant. CONCLUSION: We conclude that smoking affects all the parameters of PFT and HRV. Since there is a correlation between PFT parameters (PEFR and FEV1) and HRV parameter (LF and HF), this can help us in predicting cardiac morbidity in chronic smokers. So HRV should be included as a routine test along with PFT in chronic smokers for early diagnosis of cardiac involvement.
Entities:
Keywords:
Heart rate variability; parasympathetic; pulmonary function test; smoking
Smoking is the most important risk factor for the increased lung function decline in adults and the rate of decline is proportionate to the amount of cigarette smoked.[12] In smokers, there are structural changes which are associated with functional changes.[3] Heart rate variability (HRV) measures the variation in the sinoatrial node due to the sympathovagal change.[4] The acute effect of smoking is mainly due to nicotine while the reduction in the cardiac vagal tone is responsible for chronic effects.[5]
MATERIALS AND METHODS
Study subjects
Sixty male subjects from staff members and patients of a medical college and hospital ABC were included in the study. They were divided into two groups. The test group included 30 subjects who were chronic smokers, and controls-included 30 healthy nonsmokers (in the age group of 30-50 years). Groups were matched for age, height, weight, and body surface area. Signed informed consent was taken from each patient and ethical clearance was obtained from the institute before proceeding for the investigation.
Eligibility criteria
Chronic smokers of at least 10 pack years were included. Exclusion criteria of subject selection were as follows: History of any major illness in the previous 1 year (pulmonary disease, cardiovascular disorder, any endocrine or metabolic disorder, psychiatric disorder) or use of any drug for any ailment in the last 1 month.
Study design
This was a case-control study
Procedure for HRV
First of all, the procedure for performing HRV was explained to the subjects in detail. Anthropometric parameters such as age, height, and weight were recorded. The instrument used for HRV was POLYRITE D system. The sampling rate was 256 Hz. High and low filters were set at 99 and 0.1 Hz, respectively. The screen sweep speed was kept at 30 mm/s. The electrodes, one each on the left arm and right arm and one on the left foot, were attached and recording was done in supine position. We recorded the frequency domain analysis for which 20-min recordings were taken, and data was generated by the machine. Frequency domain parameters [high frequency (HF), low frequency (LF) and low frequency/high frequency (LF/HF)] were noted. Two spectral components were measured: LF and HF. HF measures the vagal activity predominantly and LF measures both sympathetic and vagal influences. The LF/HF ratio is an index of the relative balance of sympathovagal influences on heart. Data was analyzed statistically using Student's t-test.
Procedure for pulmonary function test
The procedure for performing pulmonary function test (PFT) was explained to them in details. RMS Medspiror was used to record the PFT. The parameters studied were forced vital capacity (FVC, l), forced expiratory volume in the first second (FEV1, l), FEV1/FVC%, mid-forced expiratory flow rate of 25-75% (MFEF 25-75, l/s), peak expiratory flow rate (PEFR, l/min), and maximum voluntary ventilation (MVV, ls/min).
Prerequisite for medspiror recording
The ambient temperature was measured accurately and recorded in Medspiror. Age, sex, and height of the subject were entered in Medspiror. The parameter to be studied were selected from the menu and recorded in sequence. The procedure was explained and demonstrated in detail prior to the commencement of each test, and maximum effort on behalf of the subject was emphasized.
Statistical analysis
For analysis t-test was used to compare cases with controls. Correlation was sought out between PFT and HRV and a regression equation was drawn.
RESULTS
As shown in Table 1, FVC in the test group was lower than that in controls though not significant. FEV1 is considered to be the best spirometric index for the measurement of airflow obstruction.[6] A statistically significant difference was observed. The mean FEV
1/FVC, MFEF 25-75, PEFR, and MVV in the control group were higher than those in the test group and the difference was statistically very highly significant. The mean heart rate in the control group as shown in
Table 2 was lower than that in the test group and the difference was statistically very highly significant. RR interval is the distance between successive RR waves. A very highly significant difference was found in the RR interval. The frequency domain parameter LF was compared between smokers and nonsmokers. LF is thought to represent the sympathetic activity as deduced by some studies while some studies in contrast consider it to represent both sympathetic and parasympathetic activities. The value for the test group was not statistically significant. HF is considered to represent the parasympathetic activity. The value was statistically significant. The LF/HF ratio represents the sympathovagal balance.
Table 1
Comparison of FVC, FEV1, FEV1/FVC, MFEF 25.75, PEFR, and MVV between test and control groups
Table 2
Comparison of mean heart rates, RR interval, LF, HF, and LF/HF ratio between test and control groups
Comparison of FVC, FEV1, FEV1/FVC, MFEF 25.75, PEFR, and MVV between test and control groupsComparison of mean heart rates, RR interval, LF, HF, and LF/HF ratio between test and control groupsA statistical significant difference was seen. Spearman's correlation coefficient
[Table 3] was used for analysis of HRV and PFT in the test group; HF and LF showed a correlation coefficient of 0.378 and-0.383 with FEV1 and PEFR, respectively.
Table 3
Spearman's correlation (between PFT and HRV parameters) in the test group
Spearman's correlation (between PFT and HRV parameters) in the test groupBy applying the multiple stepwise regression analysis model as shown in Figure 1, it was found that only FEV1/FVC was having a statistically significant regression coefficient with HF; the R-value was found to be 0.425 while with other parameters, it was not found to be significant.
Figure 1
Regression coefficient between HFms^2 and FEV1/FVC
Regression coefficient between HFms^2 and FEV1/FVC
DISCUSSION
In smokers, there are structural alterations in the lungs due to the loss of lung recoil and narrowing of airways which lead to airflow obstruction.[7] This change in structure leads to change in the pulmonary function.[3]
Forced vital capacity
In our study, the FVC in the test group was lower than that in controls though not significant. Our findings were similar to the findings of Vaidya et al. whose study showed that there was no significant difference in FVC between smokers and nonsmokers.[8] Mehmet et al. found that controls had a higher FVC than smokers but the difference was not significant.[9] Studies by many showed the same result.[1011]
Forced expiratory volume in the first second
The mean FEV1 in the control group was higher than that in the test group. A statistically significant difference was observed. Similar results were presented by Padmavati et al. whose study showed a significant difference.[10] Similarly, Vaidya et al. found a significant difference in FEV1 in smokers who had a lower value compared with nonsmokers.[9] A similar result was found by various workers.[61112] Although the study by Urrutia et al. showed that smokers had lower FEV1 compared to that in nonsmokers, the difference was not significant.[12] The difference may be due to the obstructive changes which may have developed due to smoking.
FEV1/FVC ratio
The mean FEV1/FVC ratio in the control group was higher than that in the test group. The difference was statistically very highly significant. Our results were similar to results found by Urrutia et al. who found a significant difference in the FEV1/FVC ratio.Padmavati et al. showed the same result.[10]
Mid-forced expiratory flow rate 25-75%
In the present study, the mean MFEF 25-75 value in the control group was higher than that in the test group. The value was found to be statistically very highly significant. Padmavati et al. found that the cigarette smokers had lower MFEF 25-75 rates compared to nonsmokers.[11] Similar results were deduced by other workers.[811]
Peak expiratory flow rate
The mean PEFR in the control group was higher than that in the test group. The difference between the groups was statistically very highly significant, and larger than that found by other studies. Padmavati et al. found that the cigarette smokers had a lower PEFR.[11] Similar results were presented by other workers.[13-15] Airway narrowing and reduction in recoil are responsible for the reduction in flow rates.[16]
Maximum ventilator volume
The mean MVV in the control group was higher. The difference was statistically very highly significant. We shared similar findings with Padmavati et al. who found a significant difference as the cigarette smokers had lower mean MVV values than nonsmokers. This may be due to the reduction in the muscular strength of smokers.
Heart rate
The test group had a statistically very highly significant increased heart rate compared to the control group. Studies by Niedermaier et al. showed an increased heart rate in smokers compared to nonsmokers. A similar increase in the heart rate was observed by Narkiewicz et al.[17]
RR interval
A statistically very highly significant difference was found in the RR interval between test and control groups. Niedermaier et al. found a reduced heart rate in smokers compared to nonsmokers.[18]
Parameter LF
In the control group was lower than that in the test group. The value of test group was not statistically significant. LF in smokers was less compared to non smokers as reported by Lucini et al.[7]
Parameter HF
HF denotes the parasympathetic activity. The mean HF in the control group was higher than that in the test group. The value for the test group was statistically significant. Studies by Neidermaier et al. showed significantly reduced HF in smokers compared to nonsmokers.[18]
LF/HF ratio
It represents the sympathovagal balance. The mean LF/HF ratio was found to be lower in controls than the test subjects. Neidermaier et al. found a significantly increased LF/HF ratio in smokers compared to nonsmokers.[18]
CONCLUSION
Smoking affects all the parameters of PFT and HRV. Since there is a correlation between PFT parameters (PEFR and FEV1) and HRV parameter (LF and HF), this can help us in predicting cardiac morbidity in chronic smokers. So HRV should be included as a routine test along with PFT in chronic smokers for early diagnosis of cardiac involvement.
Authors: Isabel Urrutia; Alberto Capelastegui; José María Quintana; Nerea Muñiozguren; Xavier Basagana; Jordi Sunyer Journal: Eur J Public Health Date: 2005-04 Impact factor: 3.367
Authors: K Narkiewicz; P J van de Borne; M Hausberg; R L Cooley; M D Winniford; D E Davison; V K Somers Journal: Circulation Date: 1998-08-11 Impact factor: 29.690
Authors: O N Niedermaier; M L Smith; L A Beightol; Z Zukowska-Grojec; D S Goldstein; D L Eckberg Journal: Circulation Date: 1993-08 Impact factor: 29.690
Authors: Sara H Downs; Otto Brändli; Jean-Pierre Zellweger; Christian Schindler; Nino Künzli; Margaret W Gerbase; Luc Burdet; Robert Bettschart; Elisabeth Zemp; Martin Frey; Roland Keller; Jean-Marie Tschopp; Philippe Leuenberger; Ursula Ackermann-Liebrich Journal: Respir Res Date: 2005-05-26
Authors: M S Bianchim; E F Sperandio; G S Martinhão; A C Matheus; V T Lauria; R P da Silva; R C Spadari; A R T Gagliardi; R L Arantes; M Romiti; V Z Dourado Journal: Braz J Med Biol Res Date: 2016-02-02 Impact factor: 2.590