Obesity and physical inactivity are major public health concerns, associated with increased risk of cardiovascular disease and mortality. Autonomic nervous system (ANS) dysfunction, characterized by altered autonomic modulation, contributes to these conditions. Heart rate variability (HRV), a non-invasive measure of ANS activity, has been linked to body mass index (BMI) and exercise. Over the past two decades, a notable connection has been established between the autonomic nervous system and cardiovascular mortality, including the risk of sudden cardiac death1-4. The most widely used method to classify weight status and risk of disease is the body mass index (BMI), which is equal to weight/ height in kg/m2. Central (primarily visceral) obesity (high ratio of the circumference of the waist to the circumference of the hips [waist-to-hip ratio], >0.9 in women and 1.0 in men) is independently associated with a higher risk for metabolic syndrome, diabetes mellitus, hyperandrogenism in women, and cardiovascular disease. The prevalence of obesity has increased dramatically over the past 3 decades5. The recent increase in obesity can be attributed to a combination of excess caloric intake and decreasing physical activity5. Although body weight is not a precise indicator of excess fat, it remains a commonly used metric. In epidemiological studies it is conventional to accept ±2 SD (standard deviations) from the median weight for height as a cut-off point for obesity. For adults, some people calculate various other indicators such as Body mass index, Ponderal index, Brocca index, Lorentz's formula, Corpulence index etc. Waist circumference is measured at the midpoint between the lower edge of the rib cage and the iliac crest. This easy and convenient measurement, independent of height, closely correlates with BMI and WHR and serves as a rough indicator of intra-abdominal fat and overall body fat. Variations in waist circumference can indicate changes in risk factors for cardiovascular and other chronic diseases. There is an increased risk of metabolic complications for men with a waist circumference~ 102 cm, and women with a waist circumference~ 88 cm 6,7,. Heart rate variability (HRV) refers to the variations in the time intervals between consecutive heart beats. HRV is an emergent property of interdependent governing systems which operate on different time scales to help adapt to environmental and psychological challenges. HRV reflects the regulation of autonomic balance, blood pressure (BP), gas exchange, gut function, heart function, vascular tone (the diameter of blood vessels that controls BP), and potentially facial muscle activity8. High frequency heart rate variability (HF-HRV), a measure of cardiac vagal tone is positively correlated with healthy cardiac function and longevity whereas low HF-HRV predicts increased risk for all-cause mortality and mortality following a fatal myocardial infarction. HRV indicators are classified as either time-domain or frequency-domain based on whether they compute the time difference between consecutive RR intervals or the power distribution (variance) as a function of the frequency of the RR interval time difference9.

Aim and Objectives: This study was aimed to evaluate the Heart Rate Variability in normal adults v/s overweight/obese adults during pre and post exercise period. Our objectives were to calculate BMI on the basis of anthropometric measurements and classify them into normal and obese/overweight individuals and then to measure heart rate variability during pre and post exercise to compare HRV between study group and control group pre and post exercise period.

A case control study was conducted from 2023-2024 on 170 subjects. Study was conducted in Department of Physiology to examine HRV by computerized Physiograph (Exercise physiology system -Ad Company) & stationary bicycle Ergometer (Viva Fitness Company). We included subjects willing to participate and those who gave written informed consent. We included of age group between 18-35 years of both the genders. We excluded the subjects with Comorbid cardiovascular diseases such as ischemic heart disease, cerebrovascular disease, diabetes mellitus, hypertension, lung disease and nephropathy, known Smokers, alcoholics and on any drugs affecting the autonomic function. Candidates those who met the inclusion criteria and willing to give the consent were recruited for the study. Anthropometric measurements Like Weight (kg), height (cm), waist circumference (cm) hip circumference (cm) were collected using standardized instruments. After that BMI was calculated and classified respondents according to WHO classification along with waist hip ratio. BMI>25kg/m2 based on Asian pacific guidelines were taken as cases whereas BMI between 18.5-24.9 were taken as control. On examination day, the subject was interviewed and examined before beginning of the test to verify their continued good health. Before procedure individual was asked to empty their bladder. Subject was instructed to lie in supine position comfortably and relaxed. After 10 minutes of rest at lab to get accustomed to the new environment, history was taken and Clinical examinations were carried out to exclude out any acute or chronic illness and also for autonomic dysfunction. Resting pulse rate and blood pressure using manual sphygmomanometer were recorded to determine whether the basal conditions of the subject are adequate for the experiment. HRV will be recorded in the 5 min lead-II ECG. In this study, variations in heart rate were analysed by time domain method and frequency domain method. Subjects were asked to do cycle exercise at fixed resistance of 2ohm & pedal at rate of 20-30 turns per minute for 5 minutes. Equipment used special stationary bicycle Ergometer (Viva Fitness Company). Before each test, digital metronome scale will be zeroed while the subject sits with their feet resting on the pedals. First HRV will be measured at resting stage and then after 5 minutes bicycle exercise. STATISTICAL ANALYSIS: All collected data were entered in Microsoft excel 2021 & data analysis was performed using SPSS version 25. For quantitative data mean and SD were calculated. Correlation coefficient for linear relationship between two variables was done using Spearmans correlation.

ETHICAL CONSIDERATIONS: Study was conducted after getting clearance from the institutional ethical committee. Informed written consent was obtained from all the study subjects before collecting data. Privacy and confidentiality were maintained in all stages of study. Individual data didn’t used for any other purpose.

This case control study was conducted on 170 participants (85 cases and 85 controls).

Table No.1: Distribution of Respondents According to Age

TABLE No. 2: Distribution of Respondents According to Gender

Table No.3: Distribution of Respondents According to Height

Table No.4: Distribution of Respondents According to Weight

Table No.5: Distribution of Respondents According to BMI

Table No.6: Distribution of Respondents According to Their BMI Vs Personal History

TABLE NO.7: HRV Indices for Normal and Elevated BMI at rest/before exercise

TABLE NO.8: HRV Indices for Normal and Elevated BMI after exercise

Table No.9: Heart rate variability indices in group I (Normal BMI) before and after exercise.

Table No.12: Heart rate variability indices in group II (elevated BMI) before and after exercise

The correlation analysis between HRV indices and BMI reveals several significant relationships in both resting and post-exercise conditions. At rest, SDNN has a strong positive correlation with BMI (Rho = 0.730, p<0.01*), indicating that higher BMI is associated with increased SDNN. RMSSD and pNN50% also show significant positive correlations with BMI at rest (Rho = 0.221, p=0.043* and Rho = 0.533, p<0.01* respectively). Conversely, post-exercise, these correlations diminish, with RMSSD (Rho = 0.127, p=0.248) and pNN50% (Rho = 0.169, p=0.122) showing non-significant relationships. LF shows a significant negative correlation with BMI at rest (Rho = -0.251, p=0.021*), while post-exercise, this correlation is more pronounced and negative (Rho = -0.548, p<0.01*). HF exhibits significant positive correlations with BMI both at rest (Rho = 0.347, p=0.001*) and post-exercise (Rho = 0.544, p<0.01*). The LF/HF ratio shows a significant negative correlation with BMI in both conditions (Rho = -0.246, p=0.023* at rest; Rho = -0.638, p<0.01* post-exercise). These results suggest that BMI has a complex and condition-dependent relationship with HRV indices, with some indices showing significant correlations at rest and others primarily post-exercise.

This study investigated the relationship between Body Mass Index (BMI) and autonomic modulation, as assessed by Heart Rate Variability (HRV), during pre and post exercise periods. The findings of this research provide new insights into the complex interactions between body composition, physical activity, and autonomic nervous system function. The results show that BMI is associated with altered autonomic modulation, as reflected by changes in HRV parameters, both at rest and in response to exercise. Autonomic nervous system (ANS) dysfunction is linked to various diseases, and Heart Rate Variability (HRV) is a non-invasive marker of ANS function. The Pre-exercise HRV indices revealed notable differences between Group I and Group II, indicating significant variations in autonomic function. Group I exhibited higher SDNN, RMSSD, and pNN50% values, suggesting enhanced parasympathetic activity and cardiac vagal tone. Conversely, Group II showed elevated LF and lower HF values, resulting in a higher LF/HF ratio, indicative of increased sympathetic dominance and reduced parasympathetic activity.

Similarly, in a study by Rossi RC et al (2015)10 “Impact of obesity on autonomic modulation, heart rate and blood pressure in obese young people” observed that the obese group presented higher baseline BP and HR values compared to the eutrophic. Regarding autonomic modulation a significant decrease was observed in the RMSSD; SD1, HF ms and HF nu indices in the obese group, indicating a decrease in vagal activity and reduced SDNN and SD2 rates with statistical significance for the former, suggesting a reduction in overall variability. The high value of the LF nu index and decrease in Mean RR in the obese group pointed to relative sympathetic predominance in these individuals. The visual analysis of the Poincaré plot showed less dispersion of the points in the obese group.

Prasad RVMV et al (2018)11 did a study “Resting and post exercise Heart Rate Variability in pre obese individuals: a comparative study” and found that during resting state, both groups had similar HRV/min. However, control subject had higher parasympathetic tone (high RMSSD, pNN50 & HF) and low sympathetic tone (low LF & LF/HF) as compared to pre obese individuals. In the post exercise recovery period of control BMI individuals, all the indices of sympathetic measures increased and parasympathetic measures decreased significantly. However, no such changes were observed in pre obese group, except significant decrease in the HRV/min

The studies by Ariningsih DMW (2021)12 did a study “The Effectiveness Of High Intensity Interval Training On Heart Rate Variability In Overweight And Obesity” and found that on healthy subjects stated that high-intensity training with the interval training type had an effect on decreasing the value of the parasympathetic nerve indicators (SDNN, RMSSD, pNN50, HF, HF (nu)). In addition, this type of exercise also causes an increase in the value for the sympathetic nerve indicator (LF (nu)) 1 hour after the training session.

Surendran A et al (2022)13 did a study “Study of Heart Rate Variability among Normal and Overweight Individuals during Pre-and Post-Exercise Period” observed at rest, the values of HRV domains like High Frequency (HF) and RMSSD and pNN50 (Indicators of parasympathetic activity) were less and the Low Frequency (LF) and LF/HF (Indicators of sympathetic activity) were high in an overweight group compared to control. After exercise, the difference in the HRV variables became more prominent and LF/HF became significant for the overweight group compared to the control group. Correlation between HRV variables and BMI remained almost the same both in pre-and post-exercise.  WANG Y et al (2024) 14 did a study “Effects of acute endurance exercise on heart rate variability in young males with different body mass index”. In this study there was no significant difference in SDNN, LF, HF among the three groups at rest. All three groups experienced a significant decrease in SDNN, LF, HF following exercise (p 0.01) compared to the normal weight group. So, the findings of this study are consistent with previous studies, which has demonstrated that higher BMI is associated with altered autonomic function. Specifically, elevated BMI is linked to increased sympathetic activity and reduced parasympathetic tone, both at rest and in response to physical stress. The significant correlations between BMI and HRV indices in the elevated BMI group further underscore the impact of excessive body weight on autonomic regulation.

This study investigated the relationship between body mass index (BMI) and autonomic modulation, assessed by heart rate variability (HRV), during pre and post exercise periods in healthy adults. The findings suggest that BMI is significantly related to autonomic modulation, with higher BMI individuals exhibiting decreased HRV and altered autonomic function. Exercise-induced changes in HRV were also observed, with greater improvements in autonomic function seen in individuals with higher BMI. The results provide a comprehensive analysis of how BMI influences autonomic function, revealing significant differences in HRV indices between individuals with normal and elevated BMI. These findings offer valuable insights into the impact of body weight on autonomic balance and cardiovascular risk, emphasizing the physiological variations observed in response to exercise across different BMI categories. Through this analysis, the study highlights the critical role of BMI in shaping autonomic responses, which are key indicators of overall cardiovascular health.

Limitations of The Study: Although the study has a relatively large sample size, it may still be underpowered to detect small effects or interactions. The exercise protocol used may not be representative of real-world physical activity or intensity. The study only assesses pre and post-exercise periods, which may not reflect long-term autonomic modulation. The study's findings may not be generalizable to other populations, such as athletes, children, or individuals with chronic diseases.

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