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Effect of high intensity interval training on heart rate variability in type 2 diabetic patients

Dissertation
Author: Kyriakoulla Parpa
Abstract:
The purpose of this study was to examine the effect of high intensity interval training (HIIT) on cardiovascular autonomic function as determined by heart rate variability (HRV), in type 2 diabetic patients. Fourteen type 2 diabetics (Mean age ± SD = 57±6.71 years) and five aged matched controls participated in the study. Body weight, body height, body composition, resting blood pressure, resting heart rate, waist and hip circumferences were measured at baseline and at the end of the study. Participants were required to self test their glucose levels (fasting glucose) before the initial assessment as well as at the end of the study. Resting electrocardiogram (EKG) was measured at baseline and 12-weeks after training. HRV was assessed manually from calculation of the mean R-R interval and its standard deviation measured on a 5-min EKG. Type 2 diabetic participants followed a 12-week HIIT on a treadmill consisting of four 30 min sessions per week. A HIIT session involved a 3-minute warm-up period, several short (2-min), maximum-intensity (80-90%) efforts separated by moderate intensity (50-60%) recovery intervals (2-min) and a 3-minute cool down period. Results demonstrated a significantly greater HRV pre compared to post training, t (13)=-7.46, p =0.0001. HIIT resulted in significant reduction of resting heart rate (RHR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting glucose levels. In addition, HIIT resulted in significant improvement in all body composition components. Mean weight, mean body fat and mean values for hip and waist circumferences were significantly lower after 12 weeks of training. The beneficial effect on autonomic regulation as reflected in increased HRV may have clinical importance in preventing sudden cardiac death in type 2 diabetes subjects. The adherence to the exercise program of the relatively inactive and obese diabetic population was good in this study, suggesting that guided exercise protocols may have clinical importance in the prophylactic treatment of type 2 diabetes subjects. More data in a large sample of type 2 diabetes patients are needed to confirm the beneficial effects of high intensity interval training on HRV.

TABLE OF CONTENTS Page ACKNOWLEDGEMENTS vi DEDICATION vii LIST OF TABLES xi LIST OF FIGURES xii Chapter 1 INTRODUCTION 1 Statement of Purpose 6 Statistical Hypotheses 7 Limitations 7 Delimitations 8 Definition of Terms 9 Significance of the Study 11 Chapter 2 REVIEW OF LITERATURE 13 Type 2 Diabetes 13 Causes of Type 2 Diabetes 17 Lifestyle Changes 22 Physical Activity 24 Heart Rate Variability 28 Factors that Influence Heart Rate Variability 33 Measuring Heart Rate Variability 40 High Intensity Interval Training 43 Summary of the Literature 48 Chapter 3 METHODS AND PROCEDURES 49 Research Design 49 Subjects 49 Testing Protocol 51 Initial Assessment 51 Experimental Protocol 52 Instrumentation 53 Body Weight and Body Composition 53 vm

TABLE OF CONTENTS (continued) Page Heart Rate and Blood Pressure 54 EKG 54 Statistical Analysis 55 Chapter4 RESULTS 56 Testing Normality and Homogeneity ofVariance 57 Descriptive Data 58 Medical and social History 62 Descriptive Data for HRV 64 Differences in HRV between Type 2 Diabetics and 67 Reference Group Differences in HRV between Males and Females 69 Physical Characteristics pre vs. post Training 71 Intercorrelations among Physical Characteristics and HRV... 74 Intercorrelations before Training 74 Intercorrelations after Training 76 Chapter 5 DISCUSSION, RECOMMENDATIONS and CONCLUSION... 78 Recommendations 89 Conclusions 90 REFERENCES 91 APPENDICES 108 APPENDIX A: Informed Consent & Release of Liability 109 APPENDIX B: Informed Consent for Reference 113 group APPENDIX C: General Information Questionnaire 116 APPENDIX D: PAR-Q 119 IX

TABLE OF CONTENTS (continued) Page APPENDIX E Institutional Review Board Approval Letter 123 APPENDIX F: Institutional Review Board Modified Protocol 125 APPENDIX G: Raw Data 127 x

Table LIST OF TABLES Page 1. Physical Characteristics of Type 2 Diabetics (n=14) before Training 59 2. Physical Characteristics of Type 2 Diabetics (n=14) after Training 60 3. Physical Characteristics of type 2 diabetics by Gender pre and post Training 61 4. Medical/Social Characteristics of type 2 Diabetic Participants 63 5. Descriptive Statistics for R-R intervals 65 6. HRV values Pre and Post Training 66 7. HRV of type 2 diabetics and reference group 68 8. HRV of males and females at baseline and following 12-weeks 70 of training 9 Physical Characteristics of Type 2 Diabetics (n=14) Pre-Post Training 73 10 Intercorrelations among Physical Characteristics and HRV before training 75 11 Intercorrelations among Physical Characteristics and HRV after training 77 XI

LIST OF FIGURES Figure Page 1. Resting EKG, R-R intervals 52 xii

Chapter 1 INTRODUCTION Type 2 diabetes is a serious, costly disease affecting approximately 17.5 million people in the United States (American Diabetes Association, 2008). According to the American Diabetes Association the total annual economic cost of diabetes in 2007 was $174 billion (American Diabetes Association, 2008). Type 2 diabetes formerly called non-insulin-dependent diabetes or adult-onset diabetes accounts for ~90-95% of those with diabetes (American Diabetes Association, 2005). Type 2 diabetes results from an interaction of genetic and environmental factors. The cause of type 2 diabetes is a combination of insulin resistance and inadequate compensatory insulin secretion response resulting in hyperglycemia (American Diabetes Association, 2003). Symptoms of marked hyperglycemia include polydipsia, polyuria, weight loss and blurred vision. In addition chronic hyperglycemia may result in impairment of growth and susceptibility to certain infections. Long-term complications of diabetes include retinopathy, nephropathy, peripheral neuropathy, and autonomic neuropathy (American Diabetes Association, 2003). Patients with diabetes have an increased incidence of atherosclerotic cardiovascular, peripheral arterial and cerebrovascular disease. Hypertension and abnormalities of lipoprotein metabolism are also common among people with diabetes (American Diabetes Association 2003). The risk of developing Type 2 diabetes increases with age, obesity, and lack of physical activity. In addition, Type 2 diabetes is associated with a strong genetic predisposition (Lyssenko, Almgren, Anevski, Orho-Melander, Sjogren, & Saloranta, et al., 2005). 1

Type 2 diabetes can be diagnosed using any one of the following methods (American Diabetes Association, 2003): 1. Symptoms of diabetes plus casual plasma glucose concentration >200 mg/dl (11.1 mmol/1). Casual is defined as any time of day without regard to time since the last meal. The classic symptoms of diabetes include polyuria, polydipsia, and unexplained weight loss. 2. Fasting plasma glucose (FPG) >126 mg/dl (7.0 mmol/1). Fasting is defined as no caloric intake for at least eight hours. 3. Two hours postload glucose >200 mg/dl (11.1 mmol/1) during an oral glucose tolerance test (OGTT). The test should be performed as described by WHO, using a glucose load containing the equivalent of 75 g anhydrous glucose dissolved in water. Uncontrolled diabetes can be a major cause of premature mortality, stroke, cardiovascular disease, peripheral vascular disease, congenital malformations as well as long- and short-term disability (American Diabetes Association, 2005). More than 65 percent of deaths in diabetes patients are attributed to heart and vascular disease (American Diabetes Association, 2005). Much scientific data on type 2 diabetes have been published regarding the positive effects of aerobic exercise training (Tokmakidis, Zois, Volaklis, Kotsa & Touvra, 2004) as well as strength training (Brooks, Layne, Gordon, Roubenoff, Nelson & Castaneda-Sceppa, 2006) on muscle quality and whole body insulin sensitivity. In addition, it has been demonstrated that regular supervised exercise training significantly improved heart rate variability in patients with type 2 diabetes (Bhagyalakshmi, Nagaraja, Anupama, Ramesh, Prabha, Niranjan & Shreedhara, 2

2007). Heart rate variability (HRV) is defined as cyclic changes of heart periods (R-R intervals) around the mean heart rate over time (Cowan, 1995). The amount of short and long term variability in heart rate provides a measurement of autonomic nervous system (ANS) balance (Cowan, 1995). The assumption, when HRV is assessed, is that the beat- to-beat fluctuations in the rhythm of the heart provides an indirect measure of heart health, as defined by the degree of balance in sympathetic and vagus nerve activity (Cowan, 1995). Measurement and analysis of HRV can be classified into time domain analysis and frequency domain analysis (Cowan, 1995). Measurements of HRV are generally performed on the basis of 24 hour Holter recordings or on shorter periods ranging from 0.5 to 5 minutes (Sztajzel, 2004). Abnormal HRV represents an increased risk for ventricular arrhythmias, as well as total cardiovascular morbidity and mortality (Fukuta, Hayano, Ishihara, Sakata, Mukai, Ohte et al., 2003). Studies have demonstrated that exercise training increases HRV in patients after coronary angioplasty (Tygesen, Wettervik & Wennerblom, 2001), patients with coronary artery disease (Iellamo, Legramante & Massaro, 2000) and patients on hemodialysis (Deligiannis, Kouidi & Tourkantonis, 1999). Endogenous and exogenous factors can influence changes within the ANS leading to alteration of HRV responses. Variability among individuals results from physical, psychological, environmental effects as well as from variation in measurement of values. Various researchers have noted the influence of age (Choi, Hong, Nelesen, Bardwell, Natarajan, Schubert & Dimsdale, 2006), race (Choi, Hong, Nelesen, Bardwell, Natarajan, 3

Schubert & Dimsdale, 2006), and gender (Bhagyalakshmi et al., 2007) on HRV. Obesity, smoking and alcohol consumption (Kageyama, Nishikido, Honda, Kurokawa, Imai, Kobayashi et al., 1997) exercise (Niewiadomski, Gasiorowska, Krauss, Mroz & Cybulski, 2007) air pollution (Park, O'Neill, Vokonas, Sparrow & Schwartz, 2005) mental stress (Delaney & Brodie, 2000) and medications (Bonaduce, Petretta, Ianniciello, Apicella, Cavallaro & Marciano, 1997) have also been implicated as influencing HRV. Additionally, various diseases such as hypertension, heart failure, cardiac arrhythmias, and diabetes mellitus may also affect results of HRV (Liao, Carnethon, Evans, Cascio & Heiss, 2002; Iellamo, Legramante & Massaro, 2000; Tygesen, Wettervik & Wennerblom, 2001; Deligiannis, Kouidi & Tourkantonis, 1999). HRV and multiple metabolic disorders were examined by Liao et al. (1998). The investigators reported that the 2-min HRV was 40±0.60ms in individuals without metabolic disorders. In addition, they demonstrated that standard deviation of N-N intervals (SDNN) was 37±0.68ms, 35±2.22ms, and 39±0.63ms for individuals with hypertension, diabetes and dyslipidemia, respectively. Moreover, they reported that HRV was lower in individuals with multiple disorders. Individuals with diabetes and dyslipidemia demonstrated the lowest standard deviation of R-R intervals (SDRR) (Mean HRV ± SD = 30 ± 2.12ms) compared to those with hypertension and dyslipidemia (Mean HRV ± SD = 37±0.60ms) or hypertension and diabetes (Mean HRV ±SD = 31±2.02ms). No studies have been conducted to examine how high intensity interval training can affect heart rate variability in patients with type 2 diabetes. A HUT has been the basis for training athletes for years. A HUT session involves a warm-up period, several short maximum-intensity efforts separated by moderate recovery intervals, and a cool down 4

period. Researchers have demonstrated that HUT is significantly more effective than moderate intensity training, in improving V02max (Helgerud, Heydal, Wang, Karlsen, Berg, Bjerkaas, et al., 2007). In addition, it has been demonstrated that HUT induced marked increases in whole body and skeletal muscle capacity for fatty acid oxidation during exercise in moderately active women (Talanian, Galloway, Heigenhauser, Bonen & Spriet, 2007). In contrast to previous moderate-intensity research, high-intensity interval training increased end exercise V02 for the same exercise intensity (Duffield, Edge & Bishop, 2006). HUT can benefit not only healthy athletic population but also special populations (Rognmo, Hetland, Helgerud, Hoff and Slordahl, 2004). Rognmo et al. (2004) compared the effects of high intensity aerobic interval exercise to moderate intensity exercise in terms of increasing V02peak in stable coronary artery disease patients. They demonstrated that after training V02max increased by 17.9% (p=0.012) in the high intensity group and 7.9% (p=0.038) in the moderate intensity group. The authors concluded that HUT was superior to moderate exercise for increasing V02peak in stable coronary artery disease patients. Finally, it has been demonstrated that HUT was superior to moderate intensity continuous training for improving aerobic capacity, endothelial function, and quality of life in patients with post infarction heart failure (Wisloff, Stoylen, Loennechen, Bruvold, Rognmo & Haram, 2007). Therefore, extensive literature has demonstrated that exercise intensity is a key factor in improving cardiovascular capacity. A study by Puhan, Busching, VanOort, Zaugg, Schunemann and Frey (2004) showed that interval training is no less effective than high-intensity continuous training for improving health-related quality of life and exercise capacity of patients with severe chronic obstructive pulmonary disease. The authors suggested that interval exercise was 5

better tolerated, as expressed by fewer workout breaks and better adherence to exercise protocols. Statement of Purpose The goal of the project was to address the effect of interval training on cardiovascular autonomic function as determined by HRV, in type 2 diabetic patients. The following goals were addressed: 1. Describe heart rate variability in type 2 diabetes patients, between the ages of 45-65 years. 2. Describe the differences in HRV before and after 12 weeks of supervised HIIT. 3. Describe gender differences in HRV before and after 12 weeks of HIIT. 4. Present correlations between HRV and age, blood pressure and fasting glucose levels. Consistent and extensive data have indicated that low HRV is an independent risk factor for coronary heart diseased and all cause mortality (Sandercock & Brodie, 2006). Several studies demonstrated that type 2 diabetes patients have reduced HRV (Iellamo et al., 2000; Liao et al., 2002). A major source of information is the ARIC (Atherosclerosis Risk in Communities) longitudinal study which investigated the consequence of diabetes and pre-diabetic metabolic impairments on a 9-year change in HRV of 6,245 individuals. It was demonstrated that cardiac autonomic impairment was present in early stages of diabetes. In addition, autonomic cardiac function was progressively worsened in diabetic subjects (Liao et al., 2002). Individuals who engage in regular training have lower prevalence of cardiovascular risk factors. Studies have demonstrated that exercise training increases 6

HRV in patients after coronary angioplasty (Tygesen et al., 2001), patients with coronary artery disease (Iellamo et al., 2000) and patients on hemodialysis (Deligiannis et al., 1999). Finally, animal studies (Harthmann, De Angelis, Costa, Senador, Schaan, Krieger et al., 2007; Souza, Flues, Paulini, Mostarda, Rodrigues, Souza et al., 2007) suggested that decreases in baroreflex sensitivity and HRV might have been related to increased mortality in female diabetic rats while improved autonomic regulation induced by exercise training might have contributed to decreased mortality. Statistical Hypotheses The following hypotheses were tested during this investigation: 1. Type 2 diabetics will demonstrate lower HRV compared to the reference group. 2. Males will demonstrate higher HRV compared to females. 3. HRV will be significantly greater post compared to pre-training for the diabetic group. 4. HRV will be negatively correlated with SBP, DBP, RHR and fasting glucose levels. Limitations This investigation was limited because: 1. Activity levels previous to testing could not be controlled. 2. The results were limited to the validity and reliability of the testing instruments used in the study. 3. Maintenance of proper intensity while following high intensity interval training was subjected to some variability. 7

4. Disease or sickness unknown to the participant or the investigator may have affected HRV measures. 5. Differences in stress level between the initial and final assessments may have affected HRV measures. Delimitations The investigation was delimited by the following factors: 1. Participants of the study were limited to type 2 diabetics of ages 45 to 65 years. 2. The subject sample was delimited to 19 male and female volunteers with no history of chronic heart failure, atrial fibrillation, frequent ectopic beats, unstable angina, and myocardial infarction. 3. Participants of the study were limited to type 2 diabetics that were non smokers. 4. Participants were limited to type 2 diabetics with no history of orthopedic problems, or liver and renal impairment. 8

Definition of Terms Electrocardiogram (ECG): A recording of the electrical activity of the heart. Fasting plasma glucose (FPG): Fasting is defined as no caloric intake for at least 8 h. Frequency domain analysis: is a spectral analysis of an array of R-R intervals (Akselrod et al., 1985). Heart Rate Variability (HRV): HRV is defined as cyclic changes of heart periods (R- R intervals) around the mean heart rate over time (Cowan, 1995). High intensity interval training (HIIT): Exercise training that involves a warm-up period, several short maximum-intensity (80-90% of HRmax) efforts separated by moderate recovery intervals (50-60% of HRmax), and a cool down period. Maximum Heart Rate (MHR or HRmax) is the maximum heart rate that a person should achieve during maximal physical exertion. P wave: Represents the depolarization and contraction of both atria on ECG. QRS complex: Is an electrocardiographic recording of ventricular depolarization that represents the beginning of ventricular contraction. R wave: Is the first upward wave of the QRS complex. S wave: Any downward wave preceded by an upward wave. SDRR5 or SDNN5: Standard deviation of normal R-R intervals recorded for 5 minutes. Target Heart Rate: Target heart rate (THR), or training heart rate, is a desired range of heart rate reached during aerobic exercise which enables one's heart and lungs to receive the most benefit from a workout. 9

Type 2 diabetes: Is a metabolic disorder that is primarily characterized by insulin resistance, relative insulin deficiency, and hyperglycemia. Time domain analysis: calculations of HRV that is based on statistical operations on R-R intervals (Akselrod, Gordon, Madwed, Snidman, Shannon & Cohen, 1985). 10

Significance of the Study Tragically, diabetes is a global epidemic with devastating social and economic consequences (American Diabetes Association, 2008). In studying the effects of exercise on type 2 diabetes, many studies have reported positive effects of aerobic exercise training (Tokmakidis et al., 2004) as well as strength training (Brooks et ai, 2006) on muscle quality and whole body insulin sensitivity. In addition, it has been demonstrated that regular supervised exercise training significantly improved HRV in patients with type 2 diabetes (Bhagyalakshmi et al., 2007). Several studies demonstrated that type 2 diabetes patients have reduced HRV (Iellamo et al., 2000; Liao et al., 2002). Abnormal HRV represents an increased risk for ventricular arrhythmias, as well as total cardiovascular morbidity and mortality (Fukuta et al, 2003). In a review of literature a few studies reported no significant changes in the time or frequency domain measures of HRV with exercise training in type 2 diabetics (Figueroa, Baynard, Fernhall, Carhart, Kanaley, 2007; Loimaala, Huikuri, Koobi, Rinne, Nenonen & Vuori, 2003). These studies were limited by small sample size and short duration of intervention, and thus the results cannot be generalized to diabetic patients. In addition, in one of the studies (Loimaala et al., 2003) the frequency of exercise was only 2 times per week which was probably not enough to determine if a significant effect on HRV might have occurred as a result of exercise training. No studies have been conducted to assess the effects of HUT on HRV in type 2 diabetes patients. Therefore, the significance of this study is to add to the limited body of scientific knowledge regarding the effect of HUT on cardiovascular autonomic function as determined by HRV in type 2 diabetes patients. The beneficial effects in autonomic 11

regulation caused by exercise may be associated with improved prognosis of type 2 diabetes patients.

Chapter 2 REVIEW OF LITERATURE The review of literature was divided into three sections. The first section focused on type 2 diabetes and describes causes of diabetes as well as the effects of lifestyle changes and physical activity on patients with type 2 diabetes. The second section of the review summarized HRV research. In this section the factors that influence HRV and methods of measuring HRV were reviewed. The final portion of the review focused on research concerning HUT. Type II Diabetes Type 2 diabetes is a serious illness with several complications and premature mortality. Roglic et al. (2005) estimated the global number of excess deaths due to diabetes in the year 2000. Excess mortality attributable to diabetes accounted for 2-3% of deaths in poorest countries and over 8% in the U.S., Canada, and the Middle East. In addition they determined that excess mortality attributable to diabetes accounted for 6- 27% of deaths in people 35- 64 years old. Consistent and extensive data have indicated that diabetes confers an increased risk for coronary heart disease and cardiac mortality (Almda, Scharling, Jensen &Vestergaard, 2004; Fox, Sullivan, D'Agostino & Wilson, 2004; Kannel & McGee, 1979; Vaccaro, Eberly, Neaton, Yang, Riccardi & Stamler, 2004). The increased risk of myocardial infarction among diabetic patients was first demonstrated by Kennel and McGee in the Framingham Study in 1979. In this cohort, 5209 men and women were followed for 20 years. The investigators demonstrated that diabetes mellitus almost 13

doubled the relative risk of coronary heart disease and myocardial infarction. Hu et al. (2001) examined the risk of cardiovascular disease in female nurses. A total of 117,629 female nurses between the ages of 30-55 years with no cardiovascular disease were recruited in 1976 and followed for 20 years. A total of 1,508 women had diagnosed with type 2 diabetes at baseline in 1976. Twenty years later 5,894 women developed type 2 diabetes. The investigators demonstrated an increased risk of myocardial infarction among women with type 2 diabetes mellitus at baseline compared with nondiabetic women. Finally, the risk of stroke was also significantly elevated before diagnosis of diabetes. The investigators concluded that there was an elevated risk of cardiovascular disease before the clinical diagnosis of type 2 diabetes in women. They suggested that aggressive management of cardiovascular risk factors was important in individuals at increased risk for diabetes. The results of the INTERHEART case-control study of 12,461 patients demonstrated that diabetes mellitus was one of the nine variables that accounted for over 95% of the risk for future cardiovascular disease (Yusuf, Hawken, Ounpuu, et al., 2004). Type 2 diabetes is not only a predictor of myocardial infarction but also an independent determinant of long-term reinfarction and mortality (Herlitz, Malmberg, Karlson et al., 1988). Fox et al. (2004) investigated the hypothesis that duration of diabetes is an important predictor of incident coronary heart disease (CHD) among people with diabetes. They demonstrated that among 588 people with diabetes (mean age ± SD= 58 ± 9 years, 56% men), there were 86 CHD events, including 36 deaths. After adjustment for age, sex, and CHD risk factors, the risk of CHD was 1.38 times higher for each 10-year 14

increase in duration of diabetes. Also, the risk for CHD death was 1.86 times higher for the same increase in duration of diabetes. Almdal et al. (2004) conducted a population based study of 13,000 men and women to examine the impact of type 2 diabetes on cardiovascular morbidity and mortality. A total of 13,105 subjects from the Copenhagen City Heart Study were followed up prospectively for 20 years. They demonstrated that the relative risk of first incident and admission for myocardial infarction was increased 1.5 to 4.5-fold in women and 1.5 to 2-fold in men. The relative risk of first incident and admission for stroke was increased 2 to 6.5-fold in women and 1.5 to 2-fold in men. Finally, it was demonstrated that in both women and men the relative risk of death was increased 1.5 to 2 times. Finally, Vacarro et al. (2004) demonstrated that overall, diabetes and myocardial infarction were similarly strong predictors of total mortality. In their study higher mortality from noncardiovascular causes was observed in those with diabetes only. Several studies have demonstrated that people with diabetes have a higher prevalence of atypical coronary artery disease or silent myocardial ischemia (Kannel, 1986; Naka, Hiramatsu, Aizawa, Momose, Yoshizawa & Shigematsu, 1992). Silent myocardial ischemia was examined by Kannel (1986) in the Framingham study. It was demonstrated that more than one in four myocardial infarctions that occurred over 30 years in the Framingham Study were detected only because of routine biennial electrocardiographic examinations. In addition almost half were completely silent. The incidence of unrecognized infarctions was higher in women than in men. Unrecognized infarctions could as easily as recognized ones result in death, heart failure, or strokes. Naka et al. (1992) used exercise treadmill and coronary angiography to examine 15

the incidence of silent myocardial ischemia in patients with type 2 diabetes. Their results showed that ischemic ST depression was present in 41 of the 132 diabetic patients (mean age ± SD = 61 ± 4 years) and in 42 of the 140 nondiabetic control subjects (mean age ± SD = 60 ± 8 years). In addition, among "treadmill-positive" subjects, diabetic patients had a 2.2 times higher prevalence of silent myocardial ischemia compared to nondiabetic control subjects. Also, diabetic patients who received insulin had a 2.6 times higher prevalence of silent myocardial ischemia than those who did not. Finally, they demonstrated that diabetic patients with retinopathy had a 2.5 times higher prevalence of silent myocardial ischemia than those without it (p < 0.05). Silent myocardial infarction and silent exertional ischemia in patients with diabetes were examined by Giamini, Kopelman, Ingram, Swash, Mills, and Timmis (1990). They demonstrated that ST depression occurred earlier in the diabetic than in the nondiabetic group (mean ST depression ± SD =111 ± 82 s versus mean ST depression ± SD = 216 ±\62s,p< 0.005) where the anginal perceptual threshold in the diabetic group was delayed by a mean of 86 s. In addition they demonstrated that autonomic function tests were abnormal in the diabetic group. The investigators suggested that prolongation of the anginal perceptual threshold might have been due to autonomic neuropathy involving the sensory innervation of the heart. Abdulnabi, Al-Attar, Suad, Mahussain and Sadanandan (2002) used noninvasive procedures for the detection of myocardial ischemia in patients with type 2 diabetes. A total of 42 patients (aged 41-72 years) with type 2 diabetes and no clinical history of coronary heart disease were evaluated for silent myocardial ischemia by stress cardiac exercise tolerance test (ETT), 12-lead ECG, transthoracic echocardiography and stress 16

myocardial perfusion scan using technetium-99m tetrofosmin. Results demonstrated that eleven patients (26.2%) had an ischemic pattern on their ETT while echocardiography showed diastolic dysfunction in 9 (21.4%) patients. In addition the stress myocardial perfusion scan was ischemic in 3 (7.3%) patients. The investigators indicated that there was no relation between ischemic ETT and other major cardiac risk factors (hypertension, dyslipidemia, smoking, sex, duration of diabetes, BMI, and glycated hemoglobin levels). The authors concluded that the cardiac ETT was most helpful for detecting myocardial ischemia in type 2 diabetics. Finally the investigators concluded that the prevalence of myocardial ischemia was high in patients with type 2 diabetes mellitus. Causes of Diabetes Type 2 diabetes is suggested to be caused by a combination of genetic and lifestyle factors. Kaprio et al. (1992) examined the cumulative incidence and heritability for diabetes mellitus in a nationwide cohort of 13,888 Finnish twin pairs of the same gender. They demonstrated that the cumulative incidence did not differ between monozygotic and dizygotic twins. The authors concluded that both type 1 and type 2 diabetes were associated with a strong genetic predisposition. They also suggested that heritability for Type 1 diabetes was greater than that for Type 2 while at the same time environmental factors seemed to play a significant role as well. The genetic predisposition of abnormal glucose tolerance was also investigated by Poulsen, Kyvik, Vaag and Beck-Nielsen (1999). They examined the importance of genetic and environmental factors on the development of Type 2 diabetes. The investigators examined a sample of twins (n = 606) ascertained from the population- 17

based Danish Twin Register. They demonstrated that the heritability estimates for Type 2 diabetes per se was 26% and for abnormal glucose tolerance was 61%. The investigators suggested that their findings supported the notion that type 2 diabetes has a multifactorial aetiology. They concluded that genetic predisposition was important for the development of abnormal glucose tolerance and they suggested that non-genetic factors might play a predominant role in controlling whether a genetically predisposed individual develops type 2 diabetes. In addition to the genetic contribution the prevalence of type 2 diabetes increases markedly with age. Petersen, Befroy, Dufour, Dziura, Ariyan, Rothman et al. (2003) investigated differences in insulin resistance between healthy elderly and young participants matched for lean body mass and fat mass. They demonstrated that elderly participants were markedly insulin-resistant as compared with young controls, and this resistance was attributable to reduced insulin-stimulated muscle glucose metabolism. In addition they explained that these changes were associated with increased fat accumulation in muscle and liver and with an approximately 40% reduction in mitochondrial oxidative and phosphorylation activity. They suggested that their results supported the hypothesis that an age-related decline in mitochondrial function contributes to insulin resistance in the elderly. It is expected that people 65 years and older will make up most of the diabetic population in the United States in the next 25 years (Boyle, Honeycutt, Narayan, Hoerger, Geiss, Chen et al., 2001 ). Boyle et al. (2001) estimated that the largest percent increase in diagnosed diabetes will be among people 75 years and older (+271% in women and +437% in men). 18

Full document contains 149 pages
Abstract: The purpose of this study was to examine the effect of high intensity interval training (HIIT) on cardiovascular autonomic function as determined by heart rate variability (HRV), in type 2 diabetic patients. Fourteen type 2 diabetics (Mean age ± SD = 57±6.71 years) and five aged matched controls participated in the study. Body weight, body height, body composition, resting blood pressure, resting heart rate, waist and hip circumferences were measured at baseline and at the end of the study. Participants were required to self test their glucose levels (fasting glucose) before the initial assessment as well as at the end of the study. Resting electrocardiogram (EKG) was measured at baseline and 12-weeks after training. HRV was assessed manually from calculation of the mean R-R interval and its standard deviation measured on a 5-min EKG. Type 2 diabetic participants followed a 12-week HIIT on a treadmill consisting of four 30 min sessions per week. A HIIT session involved a 3-minute warm-up period, several short (2-min), maximum-intensity (80-90%) efforts separated by moderate intensity (50-60%) recovery intervals (2-min) and a 3-minute cool down period. Results demonstrated a significantly greater HRV pre compared to post training, t (13)=-7.46, p =0.0001. HIIT resulted in significant reduction of resting heart rate (RHR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and fasting glucose levels. In addition, HIIT resulted in significant improvement in all body composition components. Mean weight, mean body fat and mean values for hip and waist circumferences were significantly lower after 12 weeks of training. The beneficial effect on autonomic regulation as reflected in increased HRV may have clinical importance in preventing sudden cardiac death in type 2 diabetes subjects. The adherence to the exercise program of the relatively inactive and obese diabetic population was good in this study, suggesting that guided exercise protocols may have clinical importance in the prophylactic treatment of type 2 diabetes subjects. More data in a large sample of type 2 diabetes patients are needed to confirm the beneficial effects of high intensity interval training on HRV.