Dissertation on
LEFT VENTRICULAR HEMODYNAMICS AND
ELECTROPHYSIOLOGY IN OBESE YOUNG ADULT MALES
Submitted to
THE TAMIL NADU DR MGR MEDICAL UNIVERSITY In partial fulfillment of the requirements for the award of the degree of
M D PHYSIOLOGY (BRANCH-V)
REG.NO:
201715052
DEPARTMENT OF PHYSIOLOGY STANLEY MEDICAL COLLEGE
CHENNAI - 600 001 MAY - 2020
CERTIFICATE
This is to certify that this dissertation entitled “LEFT VENTRICULAR HEMODYNAMICS AND ELECTROPHYSIOLOGY IN OBESE YOUNG
ADULT MALES” by the Post Graduate Dr.S.SATHISHKUMAR for M.D. PHYSIOLOGY (BRANCH-V) is a bonafide record of the research done by
him in the Department of Physiology, Stanley Medical College, Chennai in partial
fulfillment of regulations of the Tamil Nadu Dr.M.G.R Medical University for the award of degree of M.D.Physiology (Branch-V) during the academic period 2017 - 2020.
Dr.R.SHANTHIMALAR, M.D., D.A., Dr.VIJI DEVANAND, M.D.,
Dean, Professor and Head,
Stanley Medical College, Department of Physiology,
Chennai - 1. Stanley Medical College,
Chennai - 1.
DECLARATION
I Dr.S.SATHISHKUMAR, solemnly declare that this dissertation entitled,
“LEFT VENTRICULAR HEMODYNAMICS AND ELECTROPHYSIOLOGY IN OBESE YOUNG ADULT MALES” is a bonafide and genuine research work
done by me in the Department of Physiology, Stanley Medical College during 2017 - 2020 under the guidance and supervision of Dr.VIJI DEVANAD, M.D.,
Professor and Head, Department of Physiology, Stanley Medical College, Chennai - 1.
The dissertation is submitted to The Tamil Nadu Dr.M.G.R Medical University, Chennai towards partial fulfillment of the University regulations for the degree of M.D. Physiology (Branch-V), examination to be held on May 2020.
Place: Chennai Signature of the Candidate
Date: 19-10-2019 (Dr.S.SATHISHKUMAR)
CERTIFICATE OF THE GUIDE
This is to certify that the dissertation titled “LEFT VENTRICULAR HEMODYNAMICS AND ELECTROPHYSIOLOGY IN OBESE YOUNG ADULT MALES” a bonafide work carried out by Dr.S.SATHISHKUMAR, Postgraduate student in the Department of Physiology, Stanley Medical College, under my supervision and guidance towards partial fulfillment of the University regulations for the degree of M.D.Physiology (Branch-V) and is being submitted to The Tamil Nadu Dr.M.G.R Medical University, Chennai.
Dr.VIJI DEVANAND, M.D., Professor and Head,
Place: Chennai Department of Physiology,
Date: 19-10-2019 Stanley Medical College,
Chennai - 1.
ACKNOWLEDGMENT
I express my profound gratitude to Dr.R.SHANTHIMALAR, M.D., D.A., Dean, Stanley Medical College, Chennai for permitting me to use all the needed resources for this dissertation work.
I also express my thanks to Dr.A.JAMILA, M.D., Vice Principal, Stanley Medical College, Chennai for her support of this dissertation work.
I am thankful to Dr.VIJI DEVANAND, M.D., Professor and Head, Department of Physiology, Stanley Medical College, Chennai for her prime guidance and enthusiastic supervision to bring this work to fruition.
I am thankful to Dr.K.LATHA M.D., Assistant Professor, Department of Physiology, Stanley Medical College, Chennai, who helped me immensely by extending her knowledge and experience during the course of the study.
I sincerely thank Dr.C.HARIHARAN, M.D., Professor and Head, Department of General Medicine, Stanley Medical College, Chennai for granting me
permission to select the study subjects from the Medicine Ward and Out-patient Department.
I sincerely thank Dr.K.KANNAN, M.D., D.M, Professor and Head, Department of Cardiology, Stanley Medical College, Chennai for granting me permission to utilize Echocardiography for this study from the Cardiology Department.
I sincerely thank Dr.P.SEENIVASAN, M.D., Professor and Head, Department of Community Medicine, Stanley Medical College, Chennai for granting me permission to select the study subjects from the Master Health Department.
I sincerely thank Dr.M.P.SARAVANAN, M.D., Professor and Head, Department of Biochemistry, Stanley Medical College, Chennai for guiding and permitting me to carry out the estimation of total cholesterol level in the Central lab, Government Stanley Medical College and Hospital, Chennai.
I am thankful to Dr.A.VIKNESH AMBAYIRAM, M.D., Assistant Professor, Department of Community Medicine, Rajah Muthiah Medical College for his statistical support and knowledge during the course of the study.
I thank all our Associate Professors, Assistant Professors and my Post Graduate Colleagues, Department of Physiology, Stanley Medical College, Chennai for being a constant source of encouragement, an inspiration not only in this study but in all my professional endeavors.
Finally, I acknowledge the immense faith of the volunteers who have participated in this study and express my gratitude for their cooperation.
I deeply thank my family members especially Parents and Sister for their moral support and love they have for me.
Above all, I thank God for his grace and blessings which helped me to complete this task successfully.
CERTIFICATE - II
This is to certify that this dissertation work titled “LEFT VENTRICULAR HEMODYNAMICS AND ELECTROPHYSIOLOGY IN OBESE YOUNG ADULT MALES” of the candidate Dr.S.SATHISHKUMAR with registration
number 201715052 for the award of M.D. PHYSIOLOGY (BRANCH-V).
I personally verified the urkund.com website for the purpose of plagiarism check.
I found that the uploaded thesis file contains from introduction to conclusion pages and the result shows 5% percentage of plagiarism in the dissertation.
Dr.VIJI DEVANAND, M.D., Professor and Head,
Place: Chennai Department of Physiology,
Date: 19-10-2019 Stanley Medical College,
Chennai - 1.
PLAGIARISM - URKUND ANALYSIS RESULT
INSTITUTIONAL ETHICS COMMITTEE CERTIFICATE
DECLARATION
I Dr.S.SATHISHKUMAR, Postgraduate student in the Department of Physiology, Stanley Medical College hereby declare that the dissertation titled
“LEFT VENTRICULAR HEMODYNAMICS AND ELECTROPHYSIOLOGY IN OBESE YOUNG ADULT MALES” is a bonafide and original work done by me under the guidance of Dr.VIJI DEVANAND, M.D., Professor and Head, Department of Physiology, Stanley Medical College, Chennai during the period 2017 – 2020.
I agree to publish 2 papers from the said dissertation work within a period of one year from the date of qualifying for the M.D degree, with me as the first author for both papers and my guide Dr.VIJI DEVANAND, M.D., and my co-guide Dr.K.LATHA, M.D., as the corresponding authors respectively.
I also declare and undertake that this dissertation either in part or full, will not be utilized by me subsequently for any purpose, without the prior permission and consent of my guide.
I also understand and agree that this declaration made by me is final and irrevocable.
Place: Chennai
Date: 19-10-2019 (Dr.S.SATHISHKUMAR)
CONTENTS
Chapter no. Title Page no.
1 INTRODUCTION 1
2 REVIEW OF LITERATURE 6
3 AIM AND OBJECTIVES 32
4 MATERIALS AND METHODS 33
5 RESULTS 49
6 DISCUSSION 71
7 CONCLUSION 78
8 SUMMARY 80
9 BIBLIOGRAPHY 83
10
ANNEXURES
I CONSENT FORM
II INFORMATION SHEET
III PROFORMA
IV MASTER CHART
LIST OF TABLES
Table no. Title
1 Classification of obesity using BMI (Asia specific criteria) 2 Time domain measures of HRV analysis
3 Frequency domain measures of HRV analysis
4 Placement of electrodes for the recording of the lead II ECG 5 Socio-demographic characteristics of the normal group 6 Socio-demographic characteristics of the overweight group 7 Socio-demographic characteristics of the obese group 8 Comparison of mean weight among the groups
9 Distribution of mean height among the groups 10 Distribution of mean BMI among the groups
11 Comparison of mean waist circumference among the groups 12 Comparison of mean hip circumference among the groups 13 Comparison of mean waist-hip ratio among the groups
14 Comparison of mean systolic blood pressure among the groups 15 Comparison of mean diastolic blood pressure among the groups 16 Comparison of mean Left ventricular mass among the groups 17 Comparison of mean LVM / Height 2.7 among the groups 18 Comparison of mean total cholesterol among the groups 19 Comparison of mean LF norm among the groups
20 Comparison of mean HF norm among the groups 21 Comparison of mean LF / HF ratio among the groups 22 Comparison of mean heart rate among the groups
23 Correlation between LVM/Height2.7 and total cholesterol among the groups
24 Correlation between LF/HF ratio and total cholesterol among the groups
LIST OF CHARTS
Chart no. Title
1 Comparison of mean weight among the groups 2 Distribution of mean height among the groups 3 Distribution of mean BMI among the groups
4 Comparison of mean waist circumference among the groups 5 Comparison of mean hip circumference among the groups 6 Comparison of mean waist-hip ratio among the groups
7 Comparison of mean systolic blood pressure among the groups 8 Comparison of mean diastolic blood pressure among the groups 9 Comparison of mean Left ventricular mass among the groups 10 Comparison of mean LVM / Height 2.7 among the groups 11 Comparison of mean total cholesterol among the groups 12 Comparison of mean LF norm among the groups
13 Comparison of mean HF norm among the groups 14 Comparison of mean LF / HF ratio among the groups 15 Comparison of mean heart rate among the groups
16 Correlation between LVM/height2.7 and total cholesterol in normal subjects
17 Correlation between LVM / Height2.7 and total cholesterol in overweight subjects
18 Correlation between LVM / Height2.7 and total cholesterol in obese subjects
19 Correlation between LF / HF ratio and total cholesterol in normal subjects
20 Correlation between LF / HF ratio and total cholesterol in overweight subjects
21 Correlation between LF / HF ratio and total cholesterol in obese subjects
LIST OF FIGURES
Figure no. Title
1 The activity of anabolic & catabolic effector pathways in energy balance 2 The pathway of excess adiposity leads to its complications
3 The pathomechanism of coronary artery disease in obesity 4 The pathomechanism of heart failure in obesity
5 Recording of Anthropometric Measurements 6 Recording of Blood Pressure in the supine posture
7 RMS Polyrite D Machine to acquire and analyze ECG data
8 Steps in recording and processing the ECG signal to obtain HRV data 9 Electrode placement for the recording of the Lead II electrocardiogram 10 Recording of Heart Rate Variability in the supine position
11 Recording of 2 (D) M-mode echocardiogram in the supine position 12 Erba (EM 360) autoanalyzer
13 Eppendorf tubes with Plasma
LIST OF ABBREVIATIONS
AgRP : Agouti-Related Peptide
BMI : Body Mass Index
DXA : Dual-energy X-ray absorptiometry EDTA : Ethylene Diamine Tetraacetic Acid
HF norm : High Frequency power in normalized units
HRV : Heart Rate Variability
IVSd : Inter-Ventricular Septal thickness at end-diastole LF norm : Low Frequency power in normalized units LVEDD : Left Ventricular End-Diastolic Dimension LVH : Left Ventricular Hypertrophy
LVMI : Left Ventricular Mass Index MC3/4R : Melanocortin 3 and 4 Receptor MCP-1 : Monocyte Chemoattractant Protein-1
NCD : Non Communicable Disease
NFHS-3 : National Family Health Survey-3
NSTEMI : Non-ST Segment Elevation Myocardial Infarction OMA : Obesity Medical Association
POMC : Pro-opiomelanocortin
PWd : Posterior Wall thickness at end-diastole PW-TDI : Pulsatile Wave Tissue Doppler Imaging QTc : QT interval corrected to the heart rate
STEMI : ST Segment Elevation Myocardial Infarction
WHO : World Health Organization
INTRODUCTION
1. INTRODUCTION
Obesity and overweight are defined as abnormal or excessive fat accumulation that may impair the health of the individual. A simple population measure of obesity is the Body Mass Index (BMI). BMI is a simple index of weight-for-height that is commonly used to classify individuals into obesity and overweight. BMI provides the most useful population-level measure of overweight and obesity as it is similar for both sexes and all ages of adults [1].
Overweight and obesity result from an energy imbalance that occurs due to eating too many calories and not doing enough physical activity to use up those calories. Globally and regionally, there has been an increased intake of energy-dense foods that are high in fat, salt, and sugars but low in vitamins, minerals and other micronutrients; and a decline in physical activity due to the increasingly sedentary nature of many forms of work, changing modes of transportation and increasing urbanization [2].
Egger and Swinburn’s ecological model represents an important new paradigm for understanding obesity and overweight as “normal physiology within a pathological environment”. Rural-urban comparisons and migration studies provide evidence for a consequence of acculturation or modernization in increasing the prevalence of obesity because of the obesogenic environment. This effect has been endorsed to a reduced level of physical activity and the dietary changes that occur with westernization [3].
Obesity has reached pandemic proportions globally, and all this evidence suggests that the circumstances are likely to get worse. The prevalence of obesity worldwide nearly tripled between 1975 and 2016. According to the World Health Organization (WHO) global estimation in 2016, 39% of adults aged 18 years and above were overweight (39% of men and 40% of women) and 13% of adults aged 18 years and above were obese (11% of men and 15% of women) [1]. In India, 11% of the adult population is overweight and 2% of the adult population is obese [4].
Obesity can be seen as the first wave of a defined group of Non-Communicable Diseases called “New World Syndrome,” creating an enormous socioeconomic and public health burden. The World Health Organization has described obesity as one of today’s most deserted public health problems, affecting every region of the globe [5].
As an end result of being overweight or obese, at least 2.8 million people die every year globally. In the South-East Asia Region, 3 lakh people die of obesity and overweight [2]. On the backcloth of World Obesity Day on October 11, experts warned that early prevention was the need of the hour to evade an entire generation from falling prey to health ailments. Increased mortality among the obese is evident for several life-threatening diseases including type 2 diabetes mellitus, cardiovascular diseases (hypertension, stroke), gallbladder disease, metabolic syndrome, hormone- sensitive and gastrointestinal cancers. Risks are also higher for some non-fatal conditions such as musclo-skeletal disorders (back pain, arthritis), infertility, psychological disorders, dyslipidemia and breathlessness [3].
In the majority of countries, women are more obese than men however male obesity has been mounting more swiftly. Education and socioeconomic background influence obesity. Reciprocally, obesity costs labor market outcomes that, in turn, contribute to reinforcing existing social inequalities. Obese people have poorer job prospects compared to normal-weight people and they are less expected to be employed. They have added difficulty in re-entering the labor market. Obese people are less prolific at work due to more sick days and fewer worked hours. They earn about 10% less than non-obese people [6].
Non-communicable diseases (NCD) have a harmful impact on individuals and families because of the loss of household income among the poor. This occurs due to high costs incurred because of unhealthy behaviors (tobacco use, use of alcohol), out- of-pocket health-care expenditure (for treatment of NCD and their complications), and loss of wages (due to disease, disability, and premature death), thus exacerbating poverty. The extended period of illnesses in NCDs affect a large number of productive periods of life, the consequent loss of productive capacity affects earnings. This combined with high health-care costs associated with NCDs, drives poor families further into poverty [4].
Overweight and obesity, as well as their related NCDs, are mostly preventable.
Compassionate environments and communities are elemental in influencing people's choices, making a healthy selection of foods and regular physical activity in preventing obesity [2].
The approaches such as universal prevention are based on a total population approach, whereas selective and targeted prevention strategies are directed at high-risk groups. The last two approaches require screening of individuals in appropriate settings such as schools to identify subjects at risk [3].
Many new policy initiatives to deal with obesity have emerged over the last few years. Countries have used a large variety of policies, including pricing and fiscal measures such as increase the price of potentially unhealthy food products, school-
based and worksite interventions, interventions in the primary care setting (e.g. prescribing physical activity), reformulation of products, changes in portion
sizes, and transport policies (e.g. subsidies for active commuting instead of cars) [6].
In recent years, a good number of countries have relied on the utilization of social media and new technologies, or have revised the arrangements for more traditional communication policies such as food labeling or regulation of marketing, to tackle the problem of obesity [6].
The achievement of weight normalization is often unrealistic and does not have to be the ultimate goal of weight reduction strategy. Moderate weight loss can have substantial health benefits. The strategies should include modification of diet, physical activity, daily habits, thoughts, pharmacotherapies and surgeries in case of morbid obesity [3]. The study by Ghanem et all showed that obese individuals have early significant changes in left ventricular wall dimensions compared with nonobese and these changes are reversible with weight reduction [7].
The present study intends to document the prevalence of cardiac and systemic hemodynamic characteristics in a population-based sample of young adult males who are particularly affected by the epidemic of obesity that is engulfing industrialized nations. This study hypothesized that in the absence of co-morbid conditions, young obese men may exhibit early alterations in left ventricular structure and function that can be associated with the development of myocardial dysfunction. This study was conducted as part of a larger study of the cardiovascular effects of obesity in young men.
The effects of obesity on left ventricular structure and function were evaluated by the use of echocardiogram and the electrophysiological changes were assessed using a heart rate variability analyzer. To support this study we intend to evaluate the lipid profile of obese adult males. These tests mentioned above are readily available in all government medical college hospitals and it can be effectively used to screen the early cardiac changes in obese individuals in addition to full medical assessment to evaluate co-morbidity such as impaired glucose tolerance or diabetes, hypertension, and dyslipidemia.
REVIEW OF
LITERATURE
2. REVIEW OF LITERATURE
Non-communicable diseases have become one of the major epidemics in the 21st century. WHO refers to non-communicable diseases as a slow-motion disaster posing a significant threat to public health globally [8].
In 2016, Out of 56.9 million reported deaths globally, 40.5 million deaths or 71% were due to non-communicable diseases [9].
In India, NCDs account for nearly 60% of premature deaths which also add to the dual burden along with communicable diseases in preventing premature deaths.
Overweight and obesity are rising health problems in India.
National Family Health Survey-3 (NFHS-3) showed that 13% of women (15- 49 yrs) and 9% of men (15-49 yrs) were overweight or obese in 2005-2006.
Overweight prevalence was higher in urban areas than in rural areas and lower in people who are involved in agriculture or manual work [10].
2.1 OBESITY
Obesity may be defined as an abnormal growth of adipose tissue due to an enlargement of fat cell size (hypertrophy) or an increase in fat cell number (hyperplasia) or both [11]. According to the World Health Organization, Obesity is defined as “abnormal or excessive fat accumulation that presents a risk to health” [12].
A more comprehensive definition of Obesity was given by Obesity Medical Association (OMA) as a “chronic, relapsing, multi-factorial, neurobehavioral disease, wherein an increase in body fat promotes adipose tissue dysfunction and abnormal fat mass physical forces, results in adverse metabolic, biomechanical, and psychosocial health consequences” [13].
2.1.1 MEASUREMENT OF OBESITY 2.1.1.1 DIRECT MEASURES
Obesity, as defined by is directly related to fat mass, the measurement of exact total fat mass, is difficult and cumbersome in regular practice. Some of the direct methods to estimate fat mass are bioelectrical impedance, hydrostatic plethysmography, isotope dilution techniques, dual x-ray absorptiometry, skinfold method, body impedance measures with over the counter scales, and air displacement plethysmography [14]. Dual-energy X-ray absorptiometry (DXA) is considered as a gold standard method [15]. These methods are difficult in practice and used mainly for research practices.
2.1.1.2 INDIRECT METHODS
Obesity is assessed using anthropometric measures that serve as proxy indicators for assessing total body fat.
2.1.1.2.1 BODY-WEIGHT
Body-weight alone cannot be considered as an indicator of measuring obesity.
But body-weight within 2 standard deviations from the median value appropriate to age or height is considered as a crude indicator for acceptable limits especially in children for assessing the weight gain or malnutrition. But the above cannot be used to define obesity.
2.1.1.2.2 BODY MASS INDEX
Body mass index (BMI) is a simple and widely used method for the assessment of total body fat mass. BMI is a value derived from the weight and height of a person.
The BMI is defined as the weight divided by the square of the height and expressed in units of kg/m2, resulting from weight in kilograms and height in meters.
BMI is used in the categorization of obesity, as given by the Asia specific criteria.
BMI (Quetelet’s Index) = Weight / Height2
Table 1: Classification of obesity using BMI (Asia specific criteria)
BMI Classification
< 18.5 Underweight
18.5 - 22.9 Normal
23-24.9 Overweight
> 25 Obesity
BMI may not correspond to the same degree of fatness in different populations due to the difference in body proportion and ethnic differences. It also has been found that for the same age, sex and BMI, South Asians have a higher body fat percentage than Caucasians. In Caucasian men, a BMI of 30 kg/m2 corresponds to 25% of body fat whereas in South-Asian men, a BMI of < 25 kg/m2 corresponds to 33 % of body fat [16].
2.1.1.2.3 SKIN FOLD THICKNESS
It is a rapid and non-invasive method of assessing body fat particularly the subcutaneous fat using calipers. The measurement may be taken at four sites-mid triceps, Subscapular, biceps, and Suprailiac regions. The summed measurements of all the 4 sites should be less than 40 mm in boys and 50mm in girls. This method lacks reliability and comparative standards [11]
2.1.1.2.4 WAIST CIRCUMFERENCE
The circumference of waist at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest is said to be the waist circumference [17].
Values > 102 cm in men and > 88 cm in women are taken as cut off points for obesity.
Waist circumference correlates with visceral fat mass compared with MRI imaging. The main disadvantage of WC is it does not account for the height of the individual [18].
2.1.1.2.5 WAIST-HIP RATIO
Hip circumference is measured at the widest part of buttocks. The values of > 1.0 in men and > 0.85 in women are considered as cutoff points for obesity.
Waist-Hip ratio is considered as a better indicator to predict cardiovascular mortality when compared to other Anthropometric indicators [18,19].
2.1.2 PATHOGENESIS
The pathogenesis of obesity is attributed to two mechanisms:
1. Sustained positive energy balance (between energy intake and energy expenditure) 2. Resetting of the bodyweight “set point” at an increased value [20].
As evolutionary physiology, Fat is stored in the body to meet the energy demands for survival during the energy depleted situations like starvation. But with excess and easy availability of calories, there is steady storage of unused fat that contributes to obesity [20]. This alteration in the energy homeostasis due to various factors plays a central role in the development of obesity which can be evident by the fact that there is a properly operating energy homeostasis system in the remarkable body-weight stability of individuals who are not obese over long periods of time [21].
2.1.2.1 ROLE OF LEPTINS
Leptin is an adipocyte hormone, which circulates at concentrations proportional to body-fat mass and plays a significant role in the relationship between obesity and energy homeostasis. Leptins communicate the energy status of the organism to the brain. Leptin receptors are found in numerous peripheral tissues, as well as in several regions of the brain, with the highest concentrations being found in the arcuate nucleus of the hypothalamus. Increased CNS leptin signaling would be interpreted as if body fat had suddenly increased, and the brain would respond by decreasing food intake with consequent weight loss. Conversely, decreased CNS leptin signaling would elicit increased food intake and weight gain. These responses are coordinated through a complex neural network involving the melanocortin system. And also with the role of other chemokines and hormones like insulin forming a vital part in the adiposity signaling [22].
2.1.2.2 ADIPOSITY SIGNALS
The neurotransmitters that are concerned with the energy homeostasis have opposite actions in two distinct groups. Certain neurotransmitters mediate the catabolic effector circuits which decrease the food intake, increase the energy expenditure and consequently induce negative energy balance. The second category includes neurotransmitters that increase food intake, decrease energy expenditure and induce positive energy balance. They are components of anabolic effector circuits.
This circuit acts according to the energy balance, maintaining a strict negative feedback control in maintaining the relatively constant level of adipocyte mass [22].
Figure.1 depicted the relationship between energy balance, adiposity signals and the activity of anabolic and catabolic effector pathways.
Figure 1: The activity of anabolic and catabolic effector pathways in energy balance
2.1.2.3 HYPOTHALAMIC CONTROL
Hypothalamus is the most important brain region involved in the control of appetite and energy metabolism. The Arcuate nucleus within the hypothalamus, in particular, is the main center controlling hunger and food intake. There are two distinct, functionally antagonistic types of neurons in the Arcuate nucleus: the Orexigenic (appetite-stimulating) neuropeptide Y (NPY) and agouti-related peptide (AgRP) expressing AgRP/NPY neurons and the Anorexigenic (appetite suppressing) pro-opiomelanocortin (POMC) expressing POMC neurons.
During well-fed state, POMC neurons cleave into an α-melanocyte stimulating hormone that activates the melanocortin 3 and 4 (MC3/4R) receptors on downstream neurons, that projects into Paraventricular nuclei too. This results in a decrease in feeding and increased energy expenditure. Whereas, during fasting, AgRP/NPY neurons are activated and lead to the release of NPY and AgRP. NPY directly stimulates food intake by activation of NPY Y1 and Y5 receptors. Also, NPY reduces energy expenditure via a Y1 receptor-mediated reduction in tyrosine hydroxylase expression in the PVN. AgRP acts as an inverse agonist of MC3/4R, in that way preventing the anorexigenic effect of α-MSH on second-order neurons. Furthermore, AgRP/NPY neurons directly inhibit POMC neurons via inhibitory γ-aminobutyric acid (GABA) action at the level of the arcuate nucleus. Apart from this, extrahepatic connections like NTS, also mediate food intake as in caloric reward [23].
2.1.2.4 GUT HORMONES
Gastrointestinal hormones act as a vital regulator of CNS-dependent energy control. Ghrelin, which is mainly secreted from the stomach during starvation, strongly stimulates feeding by activating AgRP/NPY neurons, in addition to promoting body weight gain and adiposity via direct effects on PVN neurons. Other hormones, including glucagon-like peptide 1 (GLP-1), peptide YY3-36 (PYY3-36) and cholecystokinin (CCK), are released from the intestine upon nutrient ingestion and exert anorexigenic effects in various brain regions [23,24].
2.1.2.5 REWARD SYSTEMS
The corticolimbic pathways which include the striatum, ventral tegmental area, nucleus accumbens, insular cortex, anterior cingulate cortex, and orbitofrontal cortex are responsible for reward-associated feeding behavior. The orbitofrontal cortex is associated with regulating gustatory, olfactory, visual, somatosensory function, and sensory factors, such as taste and smell [24]. The endocannabinoid and opioid systems with its wide receptors throughout CNS plays an important role in the reward-related feeding. Nucleus ambiguous plays a central role in the mechanism. It has been observed that when a µ-opioid agonist is administered in the nucleus accumbens, the expression of orexin in the hypothalamus is increased and it eventually y stimulates the preferential intake of fat diet over carbohydrate diet.
It has also been observed that t hypothalamic endocannabinoids may act via cannabinoid receptors to increase food intake through a leptin-regulated mechanism [25]. The role of dopamine and the ventro-striatal pathways through its projection into the orbitofrontal cortex plays a vital role in the reward-related feeding behavior.
2.1.2.6 NUTRIENTS IN FOOD
Weight gain and feeding patterns are mediated by the nutrient constituent of the food consumed. The amino acid L-glutamate is found to be involved in the various
physiological mechanisms including taste perception and carbohydrate metabolism.
L-glutamate has been found to have a significant role in weight reduction, fat deposition, and plasma leptin concentration [24]. Glucose in higher concentrations exhibit the feedback mechanism and inhibits food intake [26]. Dietary nutrients play a vital role in the effectiveness of dietary therapies for the treatment of obesity.
2.1.2.7 MICROBIAL FLORA
Gut microbes provide a vital contribution to the energy metabolism by an anaerobic breakdown of peptides, proteins, and fibers producing short-chain fatty acids (SCFA). Acetate, Butyrate, and Propionate are the major constituents of SCFA which play an important role in weight gain, glucose metabolism, and insulin sensitivity [27]. Low-grade inflammation is one of the hallmarks of obesity. The lipopolysaccharide (LPS) in gram-negative bacteria is found to stimulate the pro- inflammatory cytokines and thereby fat intake [27].
2.1.3 COMPLICATIONS
Excess adiposity will lead to several complications, due to the anatomical or pressure effects or due to the metabolic or physiological effects.
2.1.3.1 ANATOMICAL EFFECTS
When the energy balance is mismatched for a prolonged period, deposition of lipids mainly in the form of triglycerides occurs, which results in the increase in the volume of skeletal muscle and other viscera that induces weight gain. With weight gain over a period of time, excess lipids start to disseminate to various compartments of the body. The majority of the fat is stored in the subcutaneous compartment at various sites, with different morphology and functions [28]. A comparatively small amount of fat has been stored in the form of mesenteric and omental fat which is said to be the visceral fat. The visceral fat is mechanistically connected to many of the metabolic disturbances and adverse outcomes associated with obesity [29].
The visceral fat around the kidney plays an important role in the development of obesity-related hypertension. The fat around the laryngeal muscles obstructs the airway during sleeping and results in snoring. The Peri abdominal fat increases the intra-abdominal pressure and results in Gastroesophageal reflux, Barrett’s esophagus, adenocarcinoma of the esophagus, etc. Excess fat and weight gain increase the workload to the joints, resulting in osteoarthritis [28].
2.1.3.2 PHYSIOLOGICAL EFFECTS
Adipocytes synthesize cytokines and hormones, depending upon the location and amount of adipose tissue present. Excessive secretion of the pro-inflammatory cytokines will lead to a chronic low-grade inflammatory state in few persons with obesity [29].
It has also been found that the fatty acids are stored within the adipocytes to prevent oxidative stress that occurs due to free fatty acids in the circulation [30].
Obesity can be attributed to the misbalanced state between energy storage and expenditure i.e the energy homeostasis. During energy excess state, the sympathetic nervous system is stimulated to dissipate the excess energy, in the form of thermogenesis which occurs in cold states too. This adaptive thermogenesis serves as an important defense mechanism against obesity [31].
This enhanced sympathetic stimulation will also lead to increased lipolysis which in turn causes the release of free fatty acids, inciting oxidative stress to mitochondria and endoplasmic reticulum, resulting in pathogenic changes in both adipose and non-adipose tissue, posing significant implications in other organ systems leading to the comorbidities [30].
The elevated levels of free fatty acids, inflammatory cytokines, and lipid intermediates in non-adipose tissues contribute to impaired insulin signaling and the insulin-resistant state that is associated with obesity. This further contributes to the dyslipidemic state found in obesity [28].
Elevated bio-available levels of insulin-like growth factor 1 and other tumor- promoting molecules have been implicated in the development of some cancers [28].
The elevated sympathetic activity associated with obesity also plays a central role in the development of hypertension. Obesity and its associated implications like chronic dyslipidemic state, insulin resistance, type 2 diabetes, hypertension play a major role in the development of heart disease, stroke and chronic kidney disease that may pose a serious risk to life.
Adipokines secreted by fat cells also directly influence the hypothalamic- pituitary axis, resulting in inhibition of ovulation and infertility. Also, Obesity plays an important role in the development of polycystic ovarian syndrome leading to hyperandrogenism and menstrual irregularities [32].
The pathway by which excess adiposity leads to its complications is depicted in detail in Figure.2 below.
Figure 2: The pathway of excess adiposity leads to its complications
2.1.3.3 PSYCHOLOGICAL EFFECTS
Obesity is found to be associated with mood disorders, anxiety and other psychiatric disorders and this relation is found to be bidirectional [28]. Moreover, the majority of the medications that are used in the treatment of psychiatric disorders have been found to predispose weight gain [33].
2.1.4 OBESITY AND HEART
Obesity is regarded as one of the major risk factors for cardiovascular diseases.
Obesity leads to adverse cardiac events in various ways. These can be indirectly mediated through its risk coupled with metabolic syndromes, like dyslipidemia, hypertension, and glucose intolerance, or effects from sleep disorders associated with obesity.
Metabolic syndrome is mostly associated with abdominal obesity with the distribution of fat cells predominantly in the abdominal viscera rather than extremities.
Due to this, there is an increase in the level of various inflammatory markers which lead to the occurrence of a pro-thrombotic state.
Many adipokines and other chemical mediators like tumor necrosis factor- alpha (TNF-α), resistin, interleukin-6 (IL-6), plasminogen activator inhibitor-1, lipoprotein lipase, acetylation stimulating protein, cholesterol ester transport protein, retinol-binding protein, estrogens, leptin, angiotensinogen, and insulin-like growth factor-1 are there in increased concentrations in obese patients.
These have various adverse effects on the cardiovascular system by creating a pro-inflammatory and pro-thrombotic state as well as causing endothelial damage and vascular hypertrophy [34].
2.1.4.1 OBESITY AND ATHEROSCLEROSIS
Both obesity and atherosclerosis are considered to be mediated through the inflammatory process. The fatty tissue releases adipocytokines, which cause insulin resistance, endothelial dysfunction, hypercoagulability, and systemic inflammation, this means facilitating the atherosclerotic process. In visceral obesity, there is a release of higher amounts of inflammatory adipocytokines like TNF-α, IL-6, monocyte chemoattractant protein-1 (MCP-1), leptin, and resistin which accelerates the process of formation of atherosclerosis [35].
2.1.4.2 OBESITY AND CORONARY HEART DISEASE
Obesity is found to be an independent predictor in the development of coronary atherosclerosis. The main pathology is the mediation in the development of atheroma and plaques within coronary vasculature. Obesity accelerates the progression of atherosclerosis even before the clinical manifestation appears and this remained important even after the regulation of other risk factors like high cholesterol, hypertension, smoking, and increased HbA1c [36].
An increase in body weight by 10 kg, increases the risk of coronary artery disease by 12%. It was found that obesity is the main risk factor in the development of non-ST segment elevation myocardial infarction (NSTEMI) in the younger age population than smoking. It also has a significant relation with ST-segment elevation myocardial infarction (STEMI) [35].
The pathomechanism by which obesity leads to coronary artery disease was depicted in detail in Figure.3 below.
Figure 3: The pathomechanism of coronary artery disease in obesity
2.1.4.3 HEMODYNAMIC CHANGES AND LV REMODELING IN HEART In obesity, there is an increase in cardiac output. But the rise is not directly proportional to total fat mass because although the resting blood flow of the adipose tissues increases with food intake, with increasing obesity, the perfusion per unit mass decreases. The increased cardiac output is to meet the metabolic demands of the fat cells. This demand is mainly achieved through an increase in stroke volume [34].
As both the cardiac output and total blood volume increase, it leads to a volume overload state and there was resultant eccentric hypertrophy of the left ventricle (LV) due to the wall stress from cavity dilatation and elevated filling pressure [37,38].
But recent studies had found out that both LV cavity size and wall thickness have been increased in obesity and this increase is not only due to dilatory response but due to the effect of adipokines from fat cells. The role of leptin in the hypertrophy has been observed with the increased expression of leptin receptors in the myocytes of obese individuals.
The other factor responsible for LV hypertrophy in obesity is hyperinsulinemia which is due to the insulin resistance that occurs due to obesity. Insulin binds with the myocardial insulin-like growth factor-1 receptors that are found abundant in the myocardium.
Now with advancements in the cardiac imagings, both the pattern of eccentric, due to dilatory response and concentric, due to adipokine response have been observed in the studies [39].
2.1.4.4 OBESITY AND CARDIAC FAILURE
Obesity has been found closely related to heart failure. It has been found from Framingham heart study data that an increase in BMI by 1 kg/m2, increases the risk of heart failure by 5% in men and 7% in women. It also has been found that heart failure develops 10 years earlier for obese and overweight individuals when compared to normal-weight people [40].
Obesity results in cardiac failure through various direct and indirect mechanisms. Obesity leads to various hemodynamic changes. The increase in blood pressure associated with obesity activates the renin angiotensin-aldosterone pathway and also increases the sympathetic activity.
Obesity also results in cardiac failure indirectly by its complications like diabetes and sleep apnoea. Figure.4 shows the various pathomechanism involved in the development of cardiac failure in obese patients.
Figure 4: The pathomechanism of heart failure in obesity
Thus obesity increases both the aldosterone and mineralocorticoid receptor expression, which in turn promotes interstitial cardiac fibrosis, platelet aggregation, and endothelial dysfunction. Increased blood volume results in venous backflow, which enhances ventricular preload leading to ventricular dilation. Hypertension increases left ventricular afterload, which raises the danger of structural and electrical myocardial remodeling. This process ultimately leads to left ventricular hypertrophy followed by diastolic and later by systolic ventricular dysfunction [35]. The inflammatory mediators like TNF, adiponectin results in myocardial fibrosis and also influences the ventricular remodeling process which leads to diastolic than systolic failure [41].
2.1.4.5 OBESITY AND CARDIAC ARRHYTHMIAS
Obesity is found to be associated with the development of cardiac arrhythmias and death. According to Framingham heart study data, sudden cardiac death was 40 times higher in obese men and women [40]. Obese people exhibit 1.52 times more risk of atrial fibrillation, one of the fatal forms of cardiac arrhythmia, than people with normal weight. A rise in BMI by one unit increases the frequency of newly developed atrial fibrillation by 4% [35].
It has been observed that the epicardial fat deposition in obese patients results in the development of atrial fibrosis due to its paracrine effect. This along with the infiltration of excess adipocytes can cause heterogeneous atrial pulse conduction, e.g., anisotropy, which contributes to endocardial and epicardial electrical dissociation.
All these processes facilitate the development of atrial reentry and eventual fibrillation. The increased presence of various inflammatory cytokines (C-reactive protein, interleukin-6, and tumor necrosis factor-α) were detected in obesity. TNF-α possibly will increase the local arrhythmic vulnerability of the pulmonary vein, in that way causing atrial fibrillation. TGF-β plays a significant role in the development of myocardial fibrosis. The leptin released from adipocytes lengthens the duration of the action potential and thereby may have an arrhythmogenic effect.
Obesity may also cause autonomous nervous system dysfunction. In the case of overweight patients, excessive sympathetic activity and decreased vagal tone and consequently increased urinary excretion of norepinephrine which disturbs the cardiac rhythm resulting in arrhythmias [28,34,35].
2.1.5.1 OBESITY AND ELECTROCARDIOGRAM
In obesity, several factors, such as horizontal displacement of the heart by the elevated diaphragm, cardiac hypertrophy, increase in the distance between the heart and the electrodes, and coexisting sleep apnea/obesity/hypoventilation syndrome, tend to modify the electrocardiogram (ECG) in obese patients.
The ECG possibly will show low voltage, leftward axis, flat inferolateral T waves, enlargement of the left atrium, increased false-positive criteria for inferior wall myocardial infarction, and less occurrence of left ventricular hypertrophy than that based on echo criteria [34]. The QT interval corrected to the heart rate (QTc) is prolonged and also QT dispersion (QTd) is increased.
2.1.5.2 OBESITY AND ECHOCARDIOGRAM
Overweight and obese patients present early cardiac changes, such as a decrease of left ventricle ejection fraction, diastolic dysfunction, thickening of the interventricular septum and an increase of the left ventricular mass. The interventricular septum and an increase of the left ventricle mass both per se as well as in ratio to body surface which can be used to predict the risk and appropriate management [42]. In obesity, eccentric hypertrophy is more frequent than the concentric type. LVH is usually calculated by the left ventricular mass index (LVMI), whereby it is indexed to height2.7. This index shows a good correlation with cardiovascular mortality. Body surface area can also be used in the index.
In obesity, the prevalence of diastolic dysfunction is above 50% and shows a close correlation with the abdominal circumference. Diastolic dysfunction is demonstrated as the E/A ratio, which is the ratio of the mitral flow velocities measured in the early diastole (E) and late diastole (A). The value less than 1 indicates diastolic dysfunction, which is primarily due to a rise in the peak velocity of A. The diagnosis also requires establishing the deceleration time, i.e., the time is taken from the peak to the end of the A wave, The data on the velocities of the mitral annular longitudinal movement obtained by the tissue doppler imaging technique can be used as complementary and specification data. Left atrial volume enlargement is also often associated with diastolic dysfunction and can be considered as a marker of the latter.
At the same time, conventional echocardiography is sometimes unsuitable for the early diagnosis of systolic or diastolic dysfunction as the measurable parameters may still be in the normal range.
Color doppler imaging detects the movement and deformity of the myocardium and is thereby able to show the changes in contractility. The so-called “integrated backscatter” method is able to sense changes in the reflectivity and weakening of the myocardium.
These are mainly determined by the myocardial collagen content and are also influenced by the mass and microstructure of cardiac muscle cells. The technique mainly provides information on myocardial stiffness, contractility, and the area of fibrosis, in a noninvasive way. Pulsatile wave tissue doppler imaging (PW-TDI) technique measures the cardiac muscle movement velocity.
2.1.5.3 OBESITY AND HEART RATE VARIABILITY
Heart rate variability (HRV) represents continuous fluctuations in heart rate.
HRV usually acts as a quantitative marker of autonomic neural control of heart rate and has been shown to reflect cardiovascular health. Low HRV is associated with an increased risk of coronary heart disease and sudden cardiac death.
The HRV variables usually analyzed are the time domain measures and the frequency domain measures which are enlisted in detail the Table.2 and Table.3 below
Table 2: Time domain measures of HRV analysis
Variable Description
SDNN (ms) The standard deviation of all NN intervals
SDANN (ms) The standard deviation of the average of NN intervals in all 5 min segments of the entire recording
RMSSD (ms) The square root of the mean of the sum of the squares of differences between adjacent NN intervals
SDNN index (ms) The mean of the standard deviations of all NN intervals for all 5 min segments of the entire recording
SDSD (ms) The standard deviation of differences between adjacent NN intervals
NN50 count The number of pairs of adjacent NN intervals differing by more than 50ms in the entire recording
pNN50 (%) The NN50 count divided by the total number of all NN intervals
HRV triangular index
Total number of all NN intervals divided by the height of the histogram of all NN intervals measured on a discrete scale with bins of 7.8125 ms
TINN (ms)
The baseline width of the minimum square difference triangular interpolation of the highest peak of the histogram of all NN intervals
Differential index
Difference between the widths of the histogram of differences between adjacent NN intervals measured at selected heights
Logarithmic index
The coefficient φ of the negative exponential curve k.e- φt which is the best approximation of the histogram of absolute differences between adjacent NN intervals
Table 3: Frequency domain measures of HRV analysis
Variable Description
Total Power (ms2) Variance of NN intervals over the temporal segment (< 0.4 Hz) ULF (ms2) The power in the ultra-low frequency range (< 0.003 Hz)
VLF (ms2) The power in the very-low-frequency range (0.003 - 0.04 Hz) LF (ms2) The power in the low-frequency range (0.04 - 0.15 Hz)
HF (ms2) The power in the high-frequency range (0.15 - 0.4 Hz) LF norm (nu) LF / (Total Power - VLF) x 100
HF norm (nu) HF / (Total Power - VLF) x 100 LF / HF ratio LF / HF
In obesity, The HRV indices indicating sympathetic activity were increased whereas those indicating parasympathetic activity were decreased in obese young adults showing an autonomic imbalance in them [43,44].
2.1.5.4 OBESITY AND CHOLESTEROL LEVEL
One of the metabolic defects that ensued in obesity includes increased levels of free fatty acids resulting from insulin resistance, increased LDL-cholesterol, VLDL, and triglycerides and a decrease in HDL-cholesterol.
It is most likely that presentation of increased free fatty acids to the liver as a function of obesity is primarily responsible for the overproduction of VLDL and this is probably the key to increased LDL via the sequence:
VLDL → intermediate-density lipoprotein (IDL) → LDL
VLDL production has also been shown to be directly related to the percentage of body fat [45]. The classical dyslipidemia of obesity consists of elevated levels of triglycerides (TG), increased FFA, decreased levels of HDL-C with HDL dysfunction and slightly increased levels of LDL-C with increased small dense LDL. The concentrations of plasma apolipoprotein B (apo B) are also often increased, partly due to the hepatic overproduction of apo B containing lipoproteins [46].
2.1.5.5 HEART RATE VARIABILITY AND CHOLESTEROL LEVEL
Hyperlipidemia is known to cause depression in HRV. The mechanism of association between hyperlipidemia and depressed HRV is not clear at the moment. It is known that catecholamines can influence lipid metabolism causing increased lipolysis and free fatty acid (FFA) mobilization.
Due to FFA mobilization, there is increased uptake of FFA into tissues which leads to the increased hepatic secretion of triglyceride-rich lipoproteins into plasma leading to an increase in serum triglyceride levels. This serum triglyceride is known to produce the risk of cardiovascular effects [47].
AIM
&
OBJECTIVES
3. AIM AND OBJECTIVES
Aim:
To study the early alterations in the left ventricular structure and cardiovascular autonomic changes in obese young adult males with echocardiogram and heart rate variability analyzer and compare it with overweight and normal individuals.
Objectives:
1. To assess the left ventricular hemodynamic changes in obese young adult males using echocardiogram.
2. To study the electrophysiology of heart in obese young adult males using heart rate variability analyzer.
3. To correlate total cholesterol value with left ventricular hemodynamic and electrophysiological changes in obese young adult males.
MATERIALS
&
METHODS
4. MATERIALS AND METHODS
4.1 Study Design : Case-Control study
4.2 Duration of Study : April 2018 to March 2019 4.3 Ethical Clearance : Institutional Ethics Committee,
Stanley Medical College, Chennai.
4.4 Sample size : Total - 90 subjects
• Obese - 30 subjects
• Overweight - 30 subjects
• Normal - 30 subjects
4.5 Place of Study :
Heart Rate Variability Research Lab,
Department of Physiology, Stanley Medical College, Chennai.
Echocardiogram Department of Cardiology, Stanley Medical College, Chennai.
Total Cholesterol Central Lab,
Department of Biochemistry, Stanley Medical College, Chennai.
4.6 Subject Selection
Subjects were selected for the study from the Outpatient Department of General Medicine, Stanley Medical College. History was taken in detail after obtaining informed and written consent.
4.6.1 Inclusion Criteria
The study population consisted of 90 young adult males of 18-38 yrs.
Asia Specific Criteria
• Obese = BMI > 25
• Overweight = BMI 23 - 24.9
• Normal = BMI 18.5 - 22.9
4.6.2 Exclusion Criteria
1. Age < 18 yrs and > 38 yrs 2. Subjects with BMI < 18.4 3. Cardiac disorders
4. Diabetes Mellitus 5. Hypertension 6. Thyroid disorders 7. Psychiatric illness 8. H/O Smoking
9. Chronic Alcoholism 10. Drug abuse
11. On drugs like steroids
12. H/O any surgery for weight reduction 13. H/O Chronic treatment for any other illness
All the subjects were explained about the study and the procedure involved in this study and their consent was obtained.
4.7 History Taking
Socio-demographic details were obtained. Any present illness and a detailed history of any other illness were recorded. Personal history including Smoking, Alcoholism, Dietary habits, and Physical activity was recorded.
4.8 Clinical Examination
On barefoot with the help of Stadiometer Height was calculated in Metre (m) and by using a standardized weighing machine Weight was calculated in Kilogram (kg). Body Mass Index was calculated using Quetelet’s Index (Weight / Height2).
After recording Waist circumference in Centimetre (cm) and Hip circumference in Centimetre (cm) using inch tape, the Waist-Hip ratio was calculated. Vital signs such as Respiratory rate, Heart Rate, and Blood pressure were recorded. General examination and Systemic examination were done in a detailed manner.
Figure 5: Recording of Anthropometric Measurements
4.9 Blood Pressure Measurement
Before blood pressure measurement smoking, caffeine and exercise were avoided. Blood pressure was measured in the left arm of the subject by both palpatory and auscultatory method in the supine position. Diamond Mercury-free LED super deluxe BP apparatus with appropriate cuff size was used to measure blood pressure.
Individuals were seated calmly for at least 10 minutes in a chair. Three measurements were taken from the left arm of the subject and the average of the three readings was taken as final blood pressure. Systolic blood pressure corresponds to the point at which the appearance of Korotkoff sounds was appreciated (Phase I).
Diastolic blood pressure corresponds to the point at which the disappearance of Korotkoff sounds was appreciated (Phase V).
Figure 6: Recording of Blood Pressure in the supine posture
4.10 Heart Rate Variability 4.10.1 Equipment
RMS Polyrite D version 2.4 hardware is a computerized recording system to acquire and analyze ECG data. It is connected to a windows-based PC. The data obtained is stored in memory for analyzing in the later period. Using software the RR intervals were plotted continuously. The software is supplied with the database, filter settings, and calculation tools.
Figure 7: RMS Polyrite D Machine to acquire and analyze ECG data
The Task Force European Society of Cardiology guidelines were followed while recording and analyzing Heart Rate Variability (HRV). The strategies of obtaining the data for the Heart Rate Variability analysis were summarized in the flow chart below.
Figure 8: Steps in recording and processing the ECG signal to obtain HRV data
4.10.2 Precautions
The study was carried out between 9 am to 1 pm in the Research laboratory, Department of Physiology, Stanley Medical College to maintain the constancy of the results.
The following precautions were taken while recording the procedure.
• The lab was kept clean, unruffled and illuminated adequately.
• The temperature of the room was maintained between 25 ̊ and 28 ̊ C.
• The subjects were made comfortable and relaxed.
• The test was recorded 2-4 hours after breakfast.
• Before the test, the subjects were instructed to empty the bladder.
• Mobile phones and other non-essential electrical devices within the vicinity were switched off while recording.
• Cable loops and running cables adjacent to metallic objects as they can affect the recording signal were regularly checked and avoided.
• The skin was made oil-free for better adhesion of electrodes by rubbing the area with an alcohol prep pad or gauze pad with benzoin tincture.
• The conductive gel was used to keep the clip-type electrodes in their position and also to increase the conductivity between skin and electrodes.
4.10.3 Placement of Electrodes
Heart Rate Variability tests were computed by recording the Lead II electrocardiogram for 10 minutes for short term analysis. The placements of electrodes for the recording of ECG were as follows in Table.1 below.
Table 4: Placement of electrodes for the recording of the lead II electrocardiogram S.No Electrode Position
1 Exploring Electrode Right Forearm 2 Exploring Electrode Left Leg 3 Reference Electrode Left Forearm
Figure 9: Electrode placement for the recording of the Lead II electrocardiogram
4.10.4 Recording of Heart Rate Variability
Heart Rate Variability recording was carried out in a supine position in the awake state with eyes closed and without making any movements. The Electrocardiogram recording in normal sinus rhythm for 5 minutes was taken for analyzing Heart Rate Variability.
The Fast Fourier Transform method was used for obtaining spectral measures.
The artifacts were excluded and the inbuilt software in the analyzer displays the values of the time domain measures and frequency domain measures automatically after analysis.
Figure 10: Recording of Heart Rate Variability in the supine position
4.10.5 Parameters Studied
For calculating time-domain indices, each QRS complex was identified and the normal to normal (N-N) intervals (the intervals between adjacent QRS complex) were determined.
The following parameters were measured using heart rate variability analyzer
• Mean Heart Rate (bpm)
• Low-frequency power in normalized units [LF/(Total Power-VLF)x100] as a marker of sympathetic activity
• High-frequency power in normalized units [HF/(Total Power-VLF)x100] as a marker of parasympathetic activity
• LF/HF ratio reflects the Sympatho-Vagal balance.
4.11Echocardiogram
Left Ventricular hemodynamics of the subjects were analyzed using echocardiogram in the Department of Cardiology, Stanley Medical College with prior permission from the Head of the Department.
4.11.1Equipment
Two-dimensional (2D) M-mode transthoracic echocardiogram was used. It had a small hand-held transducer probe that generates and receives ultrasound waves in the range of 4-7 M Hz using a principle called the piezoelectric (pressure electricity) effect. The basic principle of imaging is that, while the majority of waves are absorbed by the body, those at interfaces between different tissue densities are reflected. In addition to emitting the ultrasound waves, the transducer detects the returning waves, processes the information, and displays it as characteristic images.
4.11.2 Parameters
The following parameters were studied using a two-dimensional (2D) M-mode transthoracic echocardiogram.
The Devereux formula was used to calculate the Left Ventricular Mass (g) and Left Ventricular Mass indexed to Height2.7 (g/m2.7)
4.11.2.1 DEVEREUX FORMULA
LVM (g) = 0.8[1.04{([LVEDD + IVSd + PWd]3 - LVEDD3)}] + 0.6
• LVEDD - LV end-diastolic dimension (mm)
• IVSd - Interventricular septal thickness at end-diastole (mm)
• PWd - Posterior wall thickness at end-diastole (mm)
Figure 11:Recording of 2 (D) M-mode echocardiogram in the supine position
4.12 Total Cholesterol Estimation
The plasma level of Total Cholesterol was estimated in the Central Lab with prior permission from the Professor and Head, Department of Biochemistry, Stanley Medical College.
4.12.1 Method
Cholesterol Oxidase Enzymatic method using Erba (EM 360) autoanalyzer.
Figure 12: Erba (EM 360) autoanalyzer
4.12.2 Sample Collection and Preparation
For total cholesterol analysis, the subjects were recalled with a minimum of 12 hours of fasting for the collection of blood samples. Under aseptic precautions, 5 ml of venous blood was drawn by the phlebotomy of the median cubital vein and stored in Ethylenediaminetetraacetic acid (EDTA) containing vials.
The blood samples were centrifuged at 3000 revolutions per minute (RPM) for 10 minutes to separate plasma. Plasma was pipetted out into 1 ml Eppendorf tubes which were stored in the deep freezer until analyzed at 4̊ C.
Figure 13: Eppendorf tubes with Plasma
4.12.3 Principle
Measurement of total cholesterol by cholesterol oxidase enzymatic method (Du Pont Method) using Erba (EM 360) autoanalyzer was based on the principle that hydrolysis of cholesterol esters by cholesterol esterase leads to the formation of cholesterol and free fatty acid. Then cholesterol is oxidized by cholesterol oxidase into hydrogen peroxide and cholest-4-en-3-one. Hydrogen peroxide reacts with phenol and 4-amino antipyrine in the reagent to form a quinone imine dye (chromophore). The absorbance due to chromophore (A540nm-A600nm) is directly proportional to the cholesterol concentration.
4.12.4 Reference Value
The recommended reference value for adults - Total Cholesterol < 200 mg/dl 4.13 Statistical Analysis
The data obtained were analyzed using SPSS software version 20. Mean, standard deviation and the p-value were used to explain the characteristics of the study. ANOVA and Post hoc tests were chosen to find out the significant difference.
A Pearson correlation test was carried out to find the correlation between the parameters. P-value < 0.05 was taken as significant and p-value < 0.01 was taken as highly significant.
RESULTS
5. RESULTS
Table 5: Socio-demographic characteristics of the normal group
Characteristics
Normal
Mean + SD
Age (yrs) 23.13 + 3.82
Sex Male
Weight (kg) 60.89 + 5.87
Height (m) 1.69 + 0.07
BMI (kg/m2) 21.33 + 1.05
Waist Circumference (cm) 77.2 + 3.96 Hip Circumference (cm) 92.23 + 4.35
Waist-Hip ratio 0.83 + 0.05
Systolic BP (mm Hg) 116.7 + 6.74 Diastolic BP (mm Hg) 74.4 + 7.19
LVM (g) 157.57 + 5.70
LVM/Height2.7 (g/m2.7) 38.70 + 4.94 Total Cholesterol (mg/dl) 143.6 + 10.94
LF nu 59.88 + 3.44
HF nu 39.64 + 3.42
LF/HF ratio 1.53 + 0.25
Mean Heart Rate (bpm) 79.0 + 4.88
