RELATIONSHIP BETWEEN SERUM LEVEL AND IN TYPE 2 DIABETIC AND NON-DIABETIC FEMALE NIGERIANS AT ILE-IFE, SOUTH WESTERN NIGERIA

A DISSERTATION SUBMITTED TO THE NATIONAL POSTGRADUATE MEDICAL COLLEGE OF NIGERIA IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF THE FELLOWSHIP OF THE COLLEGE IN INTERNAL MEDICINE

SUBSPECIALTY: ENDOCRINOLOGY, DIABETES AND METABOLISM

CANDIDATE’S NAME: AJANI GBADEBO OLADIMEJI DAVID. MBChB (O.A.U) 2004

CANDIDATE’S NUMBER: AF/009/08/005/926

MAY, 2013

CERTIFICATION

The study reported in this dissertation was carried out by the candidate; Dr. Gbadebo Oladimeji David AJANI under our supervision at the endocrinology, diabetes and metabolism unit, Department of Medicine, Obafemi Awolowo University Teaching Hospitals’ Complex, Ile-Ife. We have also supervised the writing of the dissertation to our satisfaction and authorized the submission of the work for the Fellowship Examination in the Faculty of Internal Medicine.

NAME OF SUPERVISOR DR (MRS) R.T. IKEM (FMCP)

SIGNATURE: ------

DATE: ------

NAME OF SUPERVISOR: DR B.A. KOLAWOLE (FWACP)

SIGNATURE: ------

DATE: ------

ii

ATTESTATION BY THE HEAD OF DEPARTMENT

I certify that the work reported in this dissertation was carried out by Dr. Gbadebo Oladimeji David AJANI in the Department of Medicine, Obafemi Awolowo University Teaching Hospitals’ Complex, Ile-Ife, Osun State under my supervision and that of Dr. B.A Kolawole.

NAME: DR (MRS) R.T. IKEM (FMCP)

STATUS: Associate Professor of Medicine/ Endocrinologist,

Department of Medicine,

Obafemi Awolowo University Teaching Hospitals’Complex,

Ile-Ife, Osun State.

SIGNATURE: ------

DATE: ------

iii

DECLARATION

I hereby declare that this work is original unless otherwise acknowledged. The work has neither been presented to any other college for Fellowship award nor has it been submitted elsewhere for publication.

SIGNATURE ………………… DATE ……………………

DR. G.O.D AJANI

iv

DEDICATION

I dedicate this work to Almighty God, the author and giver of all wisdom, knowledge and understanding. To Him be all glory and honour.

v

ACKNOWLEDGEMENT

I give all glory to the Almighty God for strength, grace, wisdom, knowledge and help given to complete this work.

I sincerely acknowledge and appreciate the contributions of my supervisors and teachers; Dr.

(Mrs.) R.T Ikem and Dr. B.A Kolawole for guiding me through proposal writing, data collection, the writing of the final dissertation and especially their immense contribution to my training in endocrinology.I profoundly appreciate the contributions of all my other teachers and consultants in the Department of Medicine, OAUTHC to my training. I thank Prof. A.E Ohwovoriole, Dr. O.

Fasanmade of the EDM unit at LUTH for their valuable contributions to my training.

My heartfelt gratitude goes to Prof A. and Mrs. Akinsola who are my God parents, teachers as well as mentors for their encouragement and support at all times.

I thank Dr. A. Ajala, consultant chemical pathologist for his assistance with the laboratory work and Prof K.S Oluwadiya for his support and advice on statistical analysis. I appreciate every other person who at one point or the other contributed to the success of this work. May the almighty God bless and reward you all.

I thank my parents, Chief. & Chief (Mrs.) E.O Ajani for their support and lastly my unreserved appreciation goes to my wife and children for their endurance, patience, understanding, encouragement, prayers and support throughout the period of my residency training.

vi

TABLE OF CONTENTS

CONTENT PAGE

TITLE PAGE i

CERTIFICATION ii

ATTESTATION iii

DECLARATION iv

DEDICATION v

ACKNOWLEDGEMENT vi

TABLE OF CONTENTS vii

EXPANDED TABLE OF CONTENTS viii

LIST OF TABLES xv

LIST OF FIGURES xvii

LIST OF ABBREVIATIONS xviii

ABSTRACT xx

CHAPTER ONE: INTRODUCTION 1

CHAPTER TWO: LITERATURE REVIEW 6

CHAPTER THREE: SUBJECTS, MATERIALS AND METHODS 38

CHAPTER FOUR: RESULTS 49

CHAPTER FIVE: DISCUSSION 74

CHAPTER SIX: CONCLUSIONS AND RECOMMENDATIONS 80

REFERENCES 82

APPENDICES 93

vii

EXPANDED TABLE OF CONTENTS

CONTENT PAGE

TITLE PAGE i

CERTIFICATION ii

ATTESTATION iii

DECLARATION iv

DEDICATION v

ACKNOWLEDGEMENT vi

TABLE OF CONTENTS vii

EXPANDED TABLE OF CONTENTS viii

LIST OF TABLES xv

LIST OF FIGURES xvii

LIST OF ABBREVIATIONS xviii

ABSTRACT xx

CHAPTER ONE 1

1.0 Introduction 1

1.1.0 Research Question 3

viii

1.1.1 Null Hypothesis 3

1.1.2 Justification 4

1.2.0 Aim and Objectives 5

CHAPTER TWO 6

2.0. Literature Review 6

2.1.0 Preamble 6

2.2.0 Epidemiology 7

2.2.1 Background 7

2.2.2 Prevalence of Obesity 7

2.2.3 Prevalence of Obesity and Type 2 Diabetes 9

2.3.0 Aetiopathogenesis 10

2.3.1 Energy In – Energy Out = Energy Stored 10

2.3.2 Normal Regulation of Energy Balance 11

2.3.3 Leptin in Human Obesity 12

2.3.4 Regulation of Serum Leptin Concentration in Human 13

2.4.0 Obesity and Leptin in Type 2 Diabetes Mellitus 15

2.5.0 Environmental Aetiological Risk Factors for Obesity 16

ix

2.5.1 Syndromes Associated with Obesity 18

2.6.0 Pathologic Consequences of Obesity 19

2.6.1 The Metabolic Syndrome (MetS) 20

2.7.0 Measurement of Obesity 22

2.7.1 Body Mass Index 22

2.7.2 Waist Circumference and Waist-Hip Ratio 23

2.7.3 Other Measurement of Obesity 26

2.8.0 Principle of Management of Obesity 29

2.8.1 Assessment of Risk Status 29

2.8.2 Management of Obesity 32

2.8.3 Management Strategies 32

CHAPTER THREE 38

3.0.0 Subjects, Materials and Methods 38

3.1.0 Study Design 38

3.2.0 Study Location 38

3.3.0 Study Period 38

3.4.0 Study Population 38

x

3.5.0 Sampling Method 38

3.6.0 Inclusion Criteria 39

3.7.0 Exclusion Criteria 39

3.8.0 Sample Size Determination 40

3.9.0 Materials: Equipment and Reagents 41

3.10.0 Data Collection Method 42

3.11.0 Data Collection and Collation 42

3.11.1 Measurement of Clinical and Anthropometric Parameters 43

3.11.2 Laboratory Measurements 45

3.11.3 Definition of Terms 47

3.11.4 Data Analysis 48

3.11.5 Ethical Consideration 48

CHAPTER FOUR 49

4.0 Results 49

4.1 Socio-demographic characteristics of the study population 49

4.2 Comparison of clinical parameters of the study participants 52

4.3 Comparison of the anthropometric parameters of the study participants 54

xi

4.4 Comparison of the blood pressure measurements of the study participants 56

4.5 Comparison of biochemical parameters between the obese type 2 58

diabetic and obese non-diabetic female subjects

4.6 Comparison of the biochemical parameters of all subjects 58

4.7 Relationship of Serum Leptin Levels with BMI, WC, Serum Levels, 64

HOMA-IR, and HbA1C by Group.

4.8 Relationship of HOMA-IR with BMI, WC, Serum Insulin Levels, and HbA1C 66

by Group.

4.9 Relationship between serum leptin levels and glycaemic control in subjects 68

with type 2 diabetes mellitus

4.10: Relationship between serum leptin levels and glycaemic control in 71

obese type 2 diabetic subjects

4.11: Relationship between serum leptin levels and glycaemic control in 73

non-obese type 2 diabetic subjects

CHAPTER FIVE 74

5.0 Discussion 74

5.1 Preamble 74

xii

5.2: Socio-Demographic Characteristics of Study Population 74

5.3: Clinical Characteristics of Study Population 74

5.4: Comparison of serum leptin levels in the various groups 76

5.5: Relationship between serum leptin levels and glycaemic control in female subjects 78

with type 2 diabetes

5.6: Comparison of severity of insulin resistance in the various groups 79

CHAPTER SIX 80

6.0 Conclusions and Recommendations 80

6.1 Conclusions 80

6.2 Recommendations 80

6.3 Limitations of the Study 81

REFERENCES 82

APPENDIX 1: Data Proforma 93

APPENDIX 2: Informed Consent Form 96

APPENDIX 3: Ethical Consideration Form 97

APPENDIX 4: Ethical Clearance Certificate 98

APPENDIX 5: Glucose Oxidase Method 99

APPENDIX 6: Measurement of Glycosylated Haemoglobin 101

xiii

APPENDIX 7: Lipid Profile Estimation 103

APPENDIX 8: Serum Leptin Immunoassay Test 107

APPENDIX 9: Serum Insulin Immunoassay Test 109

APPENDIX 10: Budgeted Cost of Project 111

APPENDIX 11: Raw Data 112

xiv

LIST OF TABLES

TABLE TITLE PAGE

Table 2.5.0 Drugs predisposing to Obesity and their alternative replacement drugs 17

Table 2.6.0 Pathological Consequences of Obesity 21 Table 2.7.1 Body Mass Index Associated Disease Risk 23

Table 2.7.2 Classification of Overweight and Obesity by BMI, 25

Waist Circumference and Associated Disease Risk

Table 2.7.3 Classification of Abdominal Obesity by Waist Circumference (cm) 25

Table 4.1: Comparison of social habit of the study participants

Table 4.2: Comparison of clinical parameters of the study participants 55

Table 4.3: Comparison of the anthropometric parameters of the study participants

Table 4.4: Comparison of blood pressure measurements and hypertension staging 56

among the study participants

Table 4.5: Comparison of the biochemical parameters of the study participants 57

Table 4.6: Relationship of Serum Leptin Levels with BMI, WC, 62

Serum Insulin Levels, HOMA-IR, and HbA1C by Group

Table 4.7: Relationship of HOMA-IR with BMI, WC, Serum Insulin levels, 64

and HbA1C by Group.

xv

Table 4.8: Classification of diabetes control among diabetic subjects 66

Table 4.9: Comparison of biochemical parameters between obese T2DM subjects 68

with controlled and non-controlled diabetes.

Table 4.10: Correlation between Serum Leptin Levels and HbAIC in subjects with 67

controlled and non-controlled diabetes.

Table 4.11: Comparison of biochemical parameters between non-obese T2DM subjects 70

with controlled and non-controlled diabetes

xvi

LIST OF FIGURES

FIGURE TITLE PAGE

Figure 4.1 Educational Attainment of Subjects in Each Group 52

Figure 4.2 Mean Serum Leptin Levels in the Groups 59

Figure 4.3 Mean Serum Insulin Levels in the Groups 60

xvii

LIST OF ABBREVIATIONS

ADP Air Displacement Plethysmography

ATP Adenosine Tri-Phosphate

ATP-III Adult Treatment Panel –III

BC Body Fat Composition

BIA Bioelectrical Impedance Analysis

BMC Bone Mineral Content

BMI Body Mass Index

BP Blood Pressure

CHD Coronary Heart Disease

CHF Congestive Heart Failure

CI Confidence Interval

CT Computerised Tomography

DBP Diastolic Blood Pressure

DEXA Dual Energy X-rays Absorptiometry

DM Diabetes Mellitus

ECW Extracellular Water

EDM Endocrinology Diabetes and Metabolism

EOSS Edmonton Obesity Staging System

EPIC European Prospective Investigation into Cancer and Nutrition

FFM Fat Free Mass

FPG Fasting Plasma Glucose

GOPD General Out-patient Department

HbA1c Glycosylated Haemoglobin

HC Hip Circumference

xviii

HDL High Density Lipoprotein

HOMA-IR Homeostasis Model of Assessment of Insulin Resistance

IDF International Diabetes Federation

IOTF International Obesity Task Force

JAK Janus Kinase

JNC 7 Seventh Report of the Joint National Committee on the Prevention, Detection,

Evaluation and Treatment of High Blood Pressure kD Kilo Dalton

LDL Low Density Lipoprotein

MC4R Melano-Cortin 4

MetS Metabolic Syndrome

MRI Magnetic Resonance Imaging m-RNA Messenger Ribonucleic Acid

NCD Non Communicable Diseases

NIH National Institute of Health

OB-R Lepin Receptor

OAUTHC Obafemi Awolowo University Teaching Hospitals’ Complex

PET Positron Emission Tomography

POMC Pro-hormone Pro-Opio-Melano-Cortin

PCOS Polycystic Ovarian Syndrome

PVD Peripheral Vascular Disease

SBP Systolic Blood Pressure

SD Standard Deviation

STAT Signal Transducers and Activators of Transcription

TBW Total Body Water

xix

T2DM Type 2 Diabetes Mellitus

TG Triglyceride

WC Waist Circumference

WHO World Health Organisation

WHR Waist Circumference to Hip Circumference Ratio

α – MCH Alpha Melanocyte Stimulating Hormone

xx

ABSTRACT

BACKGROUND

Obese subjects, especially females, are known to have high circulating levels of leptin which is secreted in proportion to fat mass. Leptin, in addition to its ability to inhibit energy intake and increase energy expenditure also has ability to regulate glucose metabolism. Most obese subjects are said to have leptin resistance hence this may be a risk factor for type 2 diabetes, a condition characterized by chronic hyperglycaemia as a result of impaired glucose metabolism.

This study therefore, aimed to determine the level of serum leptin and serum insulin in obese female Nigerians with type 2 diabetes mellitus, Non-obese female Nigerians with type 2 diabetes mellitus and in obese non diabetic female Nigerians in Ile-Ife in order to provide baseline data for this environment

METHODS

This cross sectional comparative hospital based study was carried out over a six month period. It involved consecutive recruitment of 60 obese type 2 diabetic females, 60 non-obese type 2 diabetic females and 60 obese non-diabetic female adults with similar age from the

Endocrinology outpatient’s clinic, General outpatient department (GOPD) and Staff clinic of

Obafemi Awolowo University Teaching Hospitals’ Complex (OAUTHC) after obtaining ethical clearance from the hospital as well as informed consent from subjects. Anthropometric parameters and other relevant clinical details of all subjects were obtained. Fasting venous blood samples were taken from all subjects for the determination of fasting plasma glucose (FPG), fasting lipid profile, glycosylated haemoglobin levels (HbA1C), fasting serum insulin and leptin concentrations. HbA1C determination was done only in diabetic subjects. In addition, insulin

xxi resistance was determined in all subjects using the homeostasis model assessment of insulin resistance (HOMA-IR). The statistical software SPSS version 17.0 was used for data analysis.

Level of statistical significance was taken as p ≤ 0.05.

RESULTS

The mean age ± SD was 52.8 ± 7.3 years for the Obese Type 2 DM group, 50.7 ± 7.3 years for the Obese non-diabetic female group and 52.6 ± 7.4 years for the Non-obese Type 2 DM group.

Mean age was not significantly different among the three groups (F = 1.509, df = 2, p = 0.224).

Mean serum leptin levels in Obese Type 2 DM females, Obese non-diabetic females and Non- obese Type 2 DM subjects were 20.61 ± 15.13(95% CI = 16.70-24.52), 20.94 ± 17.64 (95% CI =

16.38-25.50) and 7.59 ± 3.39 (95% CI = 6.72-8.47) ng/ml respectively. The mean serum levels of leptin were significantly higher among the obese Type 2 DM subjects and the obese non- diabetic subjects than in Non-obese Type 2 DM subjects (F = 18.902, df = 2, p= 0.0001). There was no statistically significant difference in serum leptin levels in Obese Type 2 DM females and

Obese non-diabetic females (p = 0.999).

The mean serum leptin levels of the obese diabetic subjects with controlled diabetes (25.81 ±

21.00 ng/ml) was higher than the mean level in those with non –controlled diabetes ( 16.90 ±

7.26 ng/ml) but this difference was not statistically significant (t = 2.040, df = 28.143, p =

0.051). Similarly, the mean serum leptin level in the non-obese diabetic subjects with controlled diabetes (8.18 ± 4.03 ng/ml) was higher than the mean level in those with non – controlled diabetes ( 7.23 ± 2.92 ng/ml) but this was not statistically significantly (t = 1.047, df

= 58, p = 0.300).

xxii

Mean serum insulin levels in Obese Type 2 DM females, Obese non-diabetic females and Non- obese Type 2 DM subjects were 23.19 ± 19.54 (95% CI =18.14-28.24), 20.67 ± 20.24 (95% CI =

15.44-25.90) and 7.51 ± 3.84 (95% CI = 6.51-8.50) µIU/ml respectively. The mean serum levels of insulin were significantly higher among the Obese Type 2 DM females and Obese non- diabetic females than in the Non-obese Type 2 DM females (F =15.838, df = 2, p = 0.0001).

However, there was no statistically significant difference in the mean serum insulin levels in

Obese Type 2 DM females and Obese non-diabetic females ( p = 0.67)

The mean levels of HOMA-IR in Obese Type 2 DM, Obese non-diabetic females and Non-obese

Type 2 DM subjects were also 8.11 ± 7.41 (95% CI = 6.20-10.03), 5.07 ± 5.25 (95% CI = 3.71-

6.42) and 2.76 ± 1.77 (95% CI = 2.31-3.22) respectively The mean serum levels of HOMA-IR) were significantly different from one subjects group to another (F= 15.143,df = 2, p =0.0001).

Moreover, mean HOMA-IR level was significantly higher in the Obese Type 2 DM female subjects than the level in the Obese non-diabetic females subjects (p = 0.032).

CONCLUSION

There was no difference in the serum levels of leptin and insulin in female obese type 2 diabetic

Nigerians and obese non-diabetic female Nigerians. Serum leptin levels appeared to be elevated in subjects with controlled diabetes than in non-controlled diabetic subjects. Therefore, serum leptin levels may not be useful to distinguish obese diabetic females from obese non-diabetic females although higher serum lepti levels may be useful for improving glycaemic control. The severity of insulin resistance was highest in obese T2DM subjects and lowest in non-obese

T2DM subjects thus implying that insulin resistance get worse with obesity.

xxiii

CHAPTER ONE

1.0 INTRODUCTION

Obesity is defined as an excess proportion of body fat relative to lean body mass of sufficient magnitude to produce adverse health consequences.1, 2 Obesity is associated with many chronic diseases including type 2 diabetes, cardiovascular disease and some cancers 3 and it is a significant risk factor for diabetes.4 Type 2 diabetes is the most common metabolic disorder worldwide,5 and its prevalence is growing at an alarming rate in both developed and developing countries.6, 7 This growth has been related to the increased prevalence of obesity (defined as body mass index [BMI] ≥30 kg/m2), a primary driver in the development of type 2 diabetes, as well as an independent health problem.7 Worldwide, approximately 90% of people with diabetes are type 2, and of these, 44% are obese or overweight.8 Globally, 23% of ischaemic heart disease burden and 7–41% of certain cancer burdens are also attributable to overweight and obesity.8

The incidence of obesity is rapidly increasing in epidemic proportions all over the world.9

Weight gain in adulthood is now common in many populations, ranging from modest gains in developing countries to a substantial percentage of body weight in some Western societies. In a recent population study in Ibadan, Nigeria, the prevalence of obesity and overweight were found to be comparable to rates seen in many industrialized countries, and rapidly emerging urbanized populations in Africa.10 In this study, the prevalence of obesity was 8.82%, overweight 17.45%, and overweight plus obesity was 26.18%. The prevalence of obesity among women was 17.27% and 2.75% among men.10 In a similar study in Ile-Ife, a semi urban region of Nigeria, women also had higher prevalence of obesity irrespective of the anthropometric indices of adiposity used.11 Therefore, it can be inferred from these findings that more Nigerian women than men are predisposed to obesity, a disease that is associated with increase morbidity and mortality. More

1 so as the major metabolic complications of obesity (type 2 diabetes and the metabolic syndrome) are predicted to be particularly burdensome.12

The rising prevalence of obesity and the human and economic costs of the disease create a need for better therapies and better understanding of the physiological processes that balance energy intake and energy expenditure. As the first obese gene product identified, leptin participates in many physiological processes. Besides its well-known effects on food intake and energy metabolism, leptin has been shown to regulate cardiovascular function, glucose and lipid metabolism.13 Leptin, a protein containing 167 amino acids, demonstrates structural similarities with the cytokine family and is mainly produced by adipocytes.14 Leptin is the primary signal from energy stores and exerts negative feedback effects on energy intake. In most cases of obesity, leptin loses the ability to inhibit energy intake and increase energy expenditure; this is termed leptin resistance.2 This may be responsible for higher levels of serum leptin in most cases of obesity. There is now a suggestion that leptin could be the link between obesity and diabetes 15 and it has been demonstrated that high serum leptin levels are associated with insulin resistance and the metabolic syndrome independent of body mass index but that these associations are significantly mediated through the effects of central obesity.16 However, another study showed that plasma leptin level is not affected by the presence of type 2 diabetes mellitus or by short-term treatment with diet or oral antidiabetic drugs but that it is directly related to glycaemic control in female patients with type 2 diabetes mellitus.17

In Italy, serum leptin levels were found to be higher in obese than in normal subjects most especially in females.18 The leptin levels were also found not to be related to the presence or absence of diabetes mellitus nor to age of subjects.18 Moreover, ethnic variations in serum leptin levels were documented with markedly higher serum leptin levels among women compared to

2 men in a study involving three different Chilean aboriginal populations,19 and also similar ethnic variations, were noted across populations in a study comparing mean plasma leptin levels of adults in Nigeria, Jamaica, and the United States, respectively.20

A recent study among non-obese Nigerian women with type 2 diabetes mellitus showed that plasma leptin levels in non-controlled diabetic subjects were significantly increased compared to that obtained for controlled diabetic subjects.21 Presently, there are no local data on the relationship between serum leptin concentration, type 2 diabetes mellitus and obesity among

Nigerians. Therefore, this study aimed to ascertain the relationship between serum leptin levels and obesity and degree of diabetic control among type 2 diabetic and non-diabetic female

Nigerians.

1.1.0 RESAERCH QUESTION: Is there any difference in the levels of serum leptin among obese, and non-obese female Nigerians with type 2 diabetes and obese non-diabetic female

Nigerians?

1.1.1 NULL HYPOTHESIS: There is no difference in the levels of serum leptin of obese female Nigerians with type 2 diabetes and obese non-diabetic female Nigerians.

3

1.1.2 JUSTIFICATION

Obesity is increasing in prevalence worldwide including Nigeria and is a major risk factor for the global pandemic of type 2 diabetes.7, 9, 10, 22, 23 Its prevalence is particularly higher among women most especially in developing countries such as Nigeria.11, 24, 25

Leptin may be a link between obesity and the occurrence of type 2 diabetes.15 Studies have shown the relationship of serum leptin levels and type 2 diabetes among obese subjects in other populations of the world with respect to insulin resistance, metabolic syndrome and control of diabetes.16, 17 Generally, serum leptin levels are higher in women than in men and there are ethnic variations in the serum leptin levels.18-20

A recent study of non-obese type 2 diabetic female Nigerians related serum leptin levels to their glycaemic control,21 however, there is presently no local study on the relationship of serum leptin levels and the prescence of type 2 diabetes among obese female subjects. This study therefore seeks to determine level and the relationship if any, of serum leptin levels and obesity in type 2 diabetic and non-diabetic obese female Nigerians.

4

1.2.0 AIM AND OBJECTIVES

GENERAL AIM:

To determine the level of serum leptin and serum insulin among three groups comprising;

(a) Obese type 2 diabetic females, (b) Obese non-diabetic females, (c) Non-obese females

with type 2 diabetes mellitus.

SPECIFIC OBJECTIVES:

1) To determine levels of serum leptin in obese type 2 diabetic females, obese non-diabetic

females and non-obese females with type 2 diabetes mellitus.

2) To compare serum leptin levels in the groups of obese type 2 diabetic females, obese

non-diabetic females, and non-obese females with type 2 diabetes mellitus.

3) To determine the relationship between serum leptin levels and glycaemic control in obese

and non-obese females with type 2 diabetes mellitus.

4) To determine and compare the severity of insulin resistance using HOMA-IR in the

groups of obese type 2 diabetic females, obese non-diabetic females and non-obese

females with type 2 diabetes mellitus with a view to determine if there is any relationship

between serum leptin levels and insulin resistance.

5

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1.0 PREAMBLE: Obesity is an energy balance regulation dysfunction that leads to fat deposition ,which increases the risk for cardiovascular, respiratory, and metabolic diseases, in particular when such deposition occurs within the abdominal cavity.26 General and in particular abdominal fat deposit, poses one of the greatest public health challenges for the 21st century with alarming trends in several parts of the world. According to the World Health Organisation

(WHO), obesity is one of the ten most preventable health risks 8, 27 and general obesity is defined as body mass index (BMI) of at least 30kg/m2..

The International Obesity Task Force (IOTF) has emphasized that the health burden of obesity would be easily predicted if the hazards of accumulating intra-abdominal fat were also monitored in addition to BMI by simple measures such as waist circumference (WC).28 Therefore, the definitions of abdominal obesity, in accordance with the report of the National Cholesterol

Education Program Adult Treatment Panel (ATP) III are WC ≥ 102 cm in men and WC ≥ 88 cm in women.28 According to Yaskin et al,29 obesity is also defined as a multisystem condition associated with an elevated risk of type 2 diabetes, coronary heart disease, dyslipidaemia, metabolic syndrome, gallstones, osteoarthritis, sleep apnea, certain cancers, and Alzheimer’s disease.

6

2.2.0 EPIDEMIOLOGY:

2.2.1 BACKGROUND

The prevalence of obesity is rising globally, independent of ethnicity, race and age, and is associated with increased mortality and morbidity.22 While there was no gender disparity in the prevalence of obesity in developed countries, the prevalence of obesity was higher among females than males in the developing countries.24 Globally, 44% of diabetes burden, 23% of ischaemic heart disease burden and 7–41% of certain cancer burdens are attributable to over- weight and obesity.8

2.2.2 PREVALENCE OF OBESITY

Obesity has reached pandemic proportions around the world and now poses one of the greatest public health challenges for the 21st century. One billion of the approximately 6.5 billion people in the world are estimated to be overweight [body mass index (BMI) > 25 kg/m2] and, of these, at least 300 million are obese (BMI > 30 kg/m2).8 These numbers are predicted to more than double to 2.3 billion overweight and 700 million obese by 2015.30

In West Africa, meta-analysis of twenty-eight studies which included thirteen studies conducted in urban settings, 13 in mixed urban/rural and two in rural setting showed that the mean body mass index ranged from 20.1 to 27.0 kg/m2.25 Prevalence of obesity in West Africa was estimated at 10.0%. Women were more likely to be obese than men in urban and rural areas respectively. Urban residents were more likely to be obese than rural residents.25 Time trend analyses also indicated that prevalence of obesity in urban West Africa more than doubled

(114%) over 15 years, accounted for almost entirely in women.25

In the absence of any standard weight for height tables for the adult population in Nigeria, early studies referred the weights of subjects studied to widely used standards given for adult

7

American subjects.31 Johnson in 1970,31 in a survey among randomly selected urban adult

Nigerians in Lagos referred the weights of his subjects to similar American average weight tables and found that 43% of 440 males and 26.5% of 476 females were overweight, while 3.1% and

14.9% of males and females respectively were obese. The results of a study by Puepet et al32 in

2002,which defined the prevalence of overweight and obesity using BMI among a sample of adult Nigerians living in Jos, indicated that overweight and obesity which were previously thought to be infrequent in the Africans, are rising in frequency, which may explain the rising trend of Non Communicable Diseases (NCD) in urban African adults. The prevalence of overweight and obesity was 21.4% (19.4% in males and 23.5% in females). Of the 21.4% overweight and obese subjects, 17.2% were overweight, while 4.2% were obese. The prevalence of overweight was 15.4% of males and 4.5% of females were definitely obese. The highest incidence of overweight and obesity were found in the 35-44 years age group. All overweight and obese subjects had abnormal waist-to-hip ratio (WHR), a parameter for abdominal fat deposition. Body mass index was found to correlate significantly with WHR.32

In recent studies in Nigeria, prevalence of obesity and overweight were also found to be comparable to rates seen in many industrialized countries, and rapidly emerging urbanized populations in Africa and women generally have higher prevalence of obesity irrespective of the anthropometric indices of adiposity used.10, 11, 33, 34 In addition, it was also shown in one of these studies that the use of BMI has a strong direct correlation with waist circumference (WC) , hip circumference (HC), Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP).11

8

2.2.3 PREVALENCE OF OBESITY AND TYPE 2 DIABETES

Generalized and abdominal obesity are associated with increased risk of cardiovascular morbidity and mortality in diabetes. A meta-analysis of long-term population studies reported a statistically significant association between obesity and type 2 diabetes such that these two conditions appear nearly identical in graphic representations of their prevalence.23 The development of obesity in early adulthood has been found to be related to a higher risk and earlier onset of type 2 diabetes than its development between 40 and 55 years of age.35 A similar report from the European Prospective Investigation into Cancer and Nutrition(EPIC)–Potsdam

Study with information on weight history has also shown that severe weight gain between ages

25 and 40 years was associated with a higher diabetes risk in men (1.5 times) and in women (4.3 times) than were stable weight in early adulthood and weight gain in later life, and that this severe weight gain resulted in an average lower age at diabetes diagnosis in men (5 years) and in women (3 years).35

In a study of a cohort of adult Nigerians with type 2 diabetes, the prevalence of obesity using

BMI was 18.6% (29.5% among females and 10.6% among males), using WC it was 71.9% among females and 21.1% among males and using WHR, it was 94.1% among females and

49.6% among males.36 It has therefore been advocated that black females with type 2 diabetes be considered as a special subgroup at risk of obesity related complications.36

9

2.3.0 AETIOPATHOGENESIS: Obesity has been thought to simply be related to an imbalance between energy intake and expenditure. However, more recent research has suggested that genetic, physiological, and behavioural factors also play a significant role in the aetiology of obesity.26, 27 Energy is consumed in diet through protein, carbohydrate, and fat intake. In the presence of excess energy intake and or reduced energy expenditure, the body will subsequently convert and store these excess energy as triglyceride in adipose tissue. Over time if the energy homeostasis continues to produce a positive energy balance, excess body fat will be stored which may lead to obesity.27

2.3.1 Energy In – Energy Out = Energy Stored

Energy homeostasis is the balance between energy intake, energy expenditure, and energy storage. Maintenance of body weight depends on the balance between energy intake and energy expenditure. Energy intake is food intake; energy expenditure is derived from complex thermogenesis processes that include basal metabolism, adaptive thermogenesis, and physical activity. Adaptive thermogenesis refers to an increase in heat production through futile metabolic cycles in response to environmental or behavioral changes (excess food consumption, change in the composition of diet, modification of ambient temperature, or a variety of pathogenic stimuli).

37 These thermogenic, metabolically futile cycles are facilitated by uncoupling proteins,1, 37, 38 which decouple oxidative phosphorylation from Adenosine tri- phosphate (ATP) generation by destabilizing mitochondrial proton gradients. In most adults, body weight is almost constant despite huge variations in daily food intake and energy expenditure.39 Therefore, complex physiological systems equilibrate energy expenditure with energy intake.

10

2.3.2 NORMAL REGULATION OF ENERGY BALANCE

Energy balance is regulated by peripheral signals (hormones) that are integrated in the brain centers, including the hypothalamus, brainstem, and reward centres, which in turn modulate feeding and energy expenditure.40, 41 Some hormones reflect the long-term nutritional status of the body (including leptin, insulin, and perhaps, ), whereas other circulating gut hormones act acutely to initiate or terminate a meal (such as ghrelin, YY, , , -like 1 and 2, and ) and result in appetite stimulation or satiety.41

The brain plays a major role in energy balance regulation as it exerts controls on both food intake and energy expenditure.26 Three brain centres as previously mentioned are particularly important in these controls, namely the hypothalamus, the dorsal vagal complex in the brainstem, and the reward system, which are inter-related structures capable of controlling energy intake as well as thermogenesis. Brain systems controlling energy intake and energy expenditure have been divided into anabolic and catabolic systems, each system comprising different types of neurons capable of controlling energy intake as well as energy expenditure. These neurons release various molecules that include Y, agouti- related peptide, melanin- concentrating hormone, the endocannabinoids, α-melanocyte-stimulating hormone, cocaine- and amphetamine-regulated transcript, corticotrophin releasing factor, thyrotropin-releasing hormone, and serotonin.

These neurosystems are modulated by short- and long term peripheral signals that report on the status of the energy stores and energy fluxes. Whereas leptin and insulin are recognized as the main long-term signals, the gastrointestinal hormones ghrelin, peptide tyrosine-tyrosine, cholecystokinin, and glucagon- like peptide 1 are known as short-term signals that inform about

11 the nutritional status. The way an organism regulates energy balance is in large part a function of its genes and the environment but to date, we can consider leptin to be the most important peripheral signal for the balance of energy homeostasis.26, 42

2.3.3 Leptin in Human Obesity

Historically in the 1970s, parabiosis studies on lean and obese mice strongly suggested that circulatory factors can influence body weight but these remained unidentified until the ob gene was identified by positional cloning in 1994 by Jeffrey M. Friedman and his team of researchers at Rockefeller University.43 This new gene was found to encode a protein containing 167 amino acids which was named leptin after the Greek word leptos meaning thin. Leptin demonstrates structural similarities with cytokine family and is mainly produced by adipocytes14, 43 and in small proportion by gastric epithelium, placenta and heart.44 As the first obese gene product identified, leptin participates in many physiological processes. Besides its well-known effects on food intake and energy metabolism, leptin has been shown to regulate cardiovascular function, glucose and lipid metabolism.13 It also has immunological and reproductive effects.

Leptin is the primary signal from energy stores and exerts negative feedback effects on energy intake. It circulates as a 16kD hormone in human plasma and its production and serum levels normally reflect the amount of fats stored in adipose tissue.27, 44 Upon binding to its hypothalamic receptor,45 activation of the Janus kinase/signal transducers and activators of transcription (JAK/STAT) pathway is responsible for leptin’s effects.46 Once leptin binds to its receptor (OB-R) in the hypothalamic arcuate nucleus, it induces the synthesis of α-melanocyte stimulating hormone (α-MSH) from the prohormone (POMC) through proteolytic cleavage mediated by the enzyme pro-hormone convertase (1PC-1). Subsequently, α-

MSH binds to the melanocortin 4 receptor (MC4R) in the paraventricular nucleus which inhibits

12 the effectors of food intake.45 In most cases of human obesity, leptin loses the ability to inhibit energy intake and increase energy expenditure; this is termed leptin resistance.2

The vast majority of obese patients are leptin insensitive (resistance) rather than leptin deficient, that is, they have an excessive amount of circulating leptin that does not appear to be functioning appropriately. However, 5 to 10% of obese study participants have relatively low levels of leptin, suggesting a reduced rate of leptin production in this subgroup.47 It has also been suggested that relatively low plasma leptin levels may play a role in the development of obesity in Pima

Indians, a population prone to obesity.48 A total absence of leptin is very rare and there are only two published reports of human leptin gene mutations which cause leptin deficiency. A homozygous frame-shift mutation in the leptin gene has been identified in 2 severely obese children from the same highly consanguineous pedigree,49 while a missense mutation in the leptin gene has been found in 3 members of a Turkish kindred who are extremely obese.50

Mutations in the are equally rare in humans. A homozygous mutation in the leptin receptor gene that results in a truncated leptin receptor has been reported in 3 morbidly obese members of a French family.51 The associations of these mutations with obesity confirms the importance of leptin in regulating energy balance in humans. However, their rarity means that the pathogenesis of obesity in most patients is not due to mutations in the leptin or leptin receptor genes.

2.3.4 Regulation of Serum Leptin Concentrations in Human: The amount of body fat and the calorie intake are the two main factors regulating the level of circulating serum leptin.

Considine et al.,52 have reported that the mean serum leptin concentrations were 7.5 ± 9.3 ng per milliliter in normal-weight subjects and 31.3±24.1 ng per milliliter in obese subjects. Generally, the serum leptin concentration increases with increasing body fat mass and the ob mRNA content

13 of adipocytes producing the leptin are twice as high in the obese subjects as in the normal weight subjects.52 .This leptin mRNA is expressed predominantly by subcutaneous rather than visceral fat cell with resultant higher circulating leptin levels in obese subjects with higher proportion of subcutaneous fat than visceral fat especially in women.53 Under conditions of regular eating cycles, leptin reflects the proportion of adipose tissue.54 However, serum leptin levels begin a steady decline from the baseline values after 12 hours of fasting, reaching a nadir at 36 hours and then subsequent restoration of normal food intake is associated with a prompt leptin rise and a return to baseline values 24 hours later.54 Circulating leptin concentration is also affected by dietary macronutrient content.55 Over a 24-hour period, plasma leptin concentrations in healthy women were lower when high-fat, low-carbohydrate meals were consumed than when low-fat, high-carbohydrate meals were consumed.55

There is a diurnal variation in the serum leptin levels which have been found to be highest between mid-night and early morning hours and lowest around noon to mid-afternoon.56 Insulin and glucocorticoid are also known to increase leptin production.57

14

2.4.0 OBESITY AND LEPTIN IN TYPE 2 DIABETES MELLITUS: It has been suggested that leptin could be the link between obesity and diabetes 15 and high serum leptin levels are known to be associated with insulin resistance and metabolic syndrome independent of BMI though these associations are significantly mediated through the effects of central obesity.16

Serum leptin levels have been reported to be lower in obese women with diabetes than in obese women without diabetes and even much lower in obese women with poorly controlled diabetes.58

However, it has also been shown in another study in a population of diabetic patients which is not gender specific that plasma leptin level is not affected by the presence of type 2 diabetes mellitus or by short-term treatment with diet or oral anti-diabetic drugs, although it has a direct relationship to glycaemic control in female patients with type 2 diabetes mellitus. 17

The association between obesity and type 2 DM is well recognized, and weight gain may precede and precipitate type 2 DM, coincide with its development, or aggravate existing DM. The fundamental basis of the association between obesity and Type 2 DM is still under scrutiny, however genetic susceptibility, environmental and dietary factors, and sedentary life style have all been implicated.36 Proposed metabolic mechanism linking the two include the effect of adipokines and their receptors and other related factors such as leptin, , and adiponectin.59

These coexisting diseases have profound impact on patient outcome as individual with type 2

DM are at particular risk of adverse consequences of obesity. The interaction of obesity and type

2 DM with other components of the metabolic syndrome result in an increase in macrovascular and microvascular complications with attendant reduction in the quality of life.60-62

15

2.5.0 Environment As Aetiological Risk Factors For Obesity

The combination of an excessive nutrient intake, alcohol consumption, smoking cessation and a sedentary lifestyle are among the environmental factors predisposing to obesity. Certain medical and mental illnesses and specific pharmaceutical substances may predispose to obesity. These illnesses include endocrinopathies (such as hypothyroidism, Cushing’s syndrome, deficiency) and also mental disorders (like bulimia nervosa and binge eating disorder).

Medications like steroids, atypical antipsychotics, some fertility , e.t,c.,(see table

2.5.0) are all known to cause obesity.

The roles of ethnic and cultural factors in the development of obesity are also very important in view of the fact that these factors are the determinants of the behaviors and practices which promote obesity.

16

Table 2.5.0 Drugs predisposing to Obesity and their alternative replacement drugs

Medication class Agents Alternatives

Steroids Glucocorticoids Asthma: inhalers Cancer chemotherapy: non- glucocorticoid based regimens Rheumatoid arthritis: methotrexate & remitting agents

Antidiabetic drugs Insulin Metformin, acarbose Sulphonylureas Thiazolidineodiones

Antiepileptic drugs Gabapentin Lamotrigine Valproic acid Topiramate

Antipsychotic agents Clozanpine Haloperidol Olanzepine, , Ziprasidone Sertindole

Antidepressants Tricyclic antidepressants MAO inhibitors Nefazodone Mirtazapine Sel serotonin reuptake I. Venlafaxine

17

2.5.1 SYNDROMES ASSOCIATED WITH OBESITY

A number of complex human syndromes with defined inheritance are associated with obesity.

These include Prader-Willi, Alström, Cohen , Laurence-Moon-Biedl, Börjeson-Forssman-

Lehmann, Fröhlich, Carpenter and Beckwith-Wisedemann’s syndromes. In the Prader-Willi syndrome, obesity coexists with short stature, mental retardation, hypogonadotropic hypogonadism, hypotonia, small hands and feet fish-shaped mouth, and hyperphagia. Most patients have a chromosome 15 deletion. Laurence-Moon-Biedl syndrome is characterized by obesity, mental retardation, retinitis pigmentosa, polydactyly, and hypogonadotropic hypogonadism. In the Alström’s syndrome, patient has early onset of truncal obesity with normal stature and occasionally short stature. There is normal intelligence, hyogonadism in male only and no distinct facial features. Its inheritance mode is also autosomal recessive.63

Carpenter syndrome is characterized by truncal and or gluteal obesity in association with normal stature, acrocephaly, flat nasal bridge, high arched palate, polydactyly, syndactyly and genum valgum. There is mild mental retardation ,primary hypogonadism and mode of inheritance is autosomal recessive. Another example of these syndromes is Cohen’s syndrome where truncal obesity co exists with short or tall stature, mild mental retardation, high nasal bridge, arched palate, open mouth and short philtrum. There is also hypotonia with narrow hand and feet, dysplastic ears, delayed puberty with or without hypogonadotropic hypogonadism. The mode of inheritance is probably autosomal recessive.63

18

2.6.0 PATHOLOGIC CONSEQUENCES OF OBESITY

Elevated body mass index, particularly that caused by abdominal or upper-body obesity, has been associated with a number of diseases and metabolic abnormalities, many of which have high morbidity and mortality (Table 2.6.0). These include hyperinsulinemia, insulin resistance, type 2 diabetes, hypertension, dyslipidemia, coronary heart disease, gallbladder disease, and certain malignancies.3, 64 Obesity is associated with an elevated risk of metabolic syndrome, gallstones, osteoarthritis, respiratory diseases such as sleep apnea, and Alzheimer’s disease.29, 65

The effects of obesity and overweight affect cardiovascular disease from several different angles, including arrhythmias, peripheral vascular disease (PVD) and stroke, sudden death, coronary heart disease (CHD) and atherosclerosis, and most predominantly hypertension and congestive heart failure (CHF).27 Other pathologic consequences of obesity include; urinary incontinence, infertility, polycystic ovarian syndrome (PCOS), gastroesophageal reflux disease, pancreatitis, nonalcoholic steatohepatitis, restrictive lung disease, obesity- hypoventilation syndrome, idiopathic intracranial hypertension (also known as pseudotumor cerebri), depression, and cataract.66 These health consequences and psychosocial problems associated with obesity will eventually lead to impaired quality of life, considerable morbidity and premature death.27, 66

19

2.6.1 The Metabolic Syndrome (MetS): This refers to a clustering of metabolic disturbances consisting of obesity, hypertension, dyslipidaemia and hyperglycaemia. According to the new

IDF metabolic syndrome world- wide definition and clinical criteria,67 for a person to be defined as having the MetS, they must have central obesity plus any two of four additional factors. These four factors are:

• Raised TG level: ≥ 1.7 mmol/l (150 mg/ dl)

• Reduced HDL-cholesterol: < 1.03 mmol/l (40 mg/dl) in males and < 1.29 mmol/ l (50 mg/ dl) in females (or specific treatment for these lipid abnormalities)

• Raised blood pressure (systolic BP ≥ 130 or diastolic BP ≥ 85 mmHg) (or treatment of previously diagnosed hypertension)

• Raised fasting plasma glucose [FPG ≥ 5.6 mmol/ l (100 mg/dl)] (or previously diagnosed type

2 diabetes).

Central obesity is determined by ethnic specific cut off point for waist circumference and the

IDF recommended cut off points for people of sub-Saharan Africa are WC ≥ 80 cm for female and WC ≥ 94 cm for male.67

20

Table 2.6.0: Pathological Consequences of Obesity System Pathology Gastrointestinal Gallstones, pancreatitis, abdominal hernia, Non-Alcoholic Fatty Liver Disease (steatosis, steatohepatitis and cirrhosis) and possibly Gastro-Esophageal Reflux Disease Endocrinology/metabolic Metabolic syndrome, insulin resistance, impaired glucose tolerance, type II diabetes mellitus, dyslipidemia, polycystic ovarian syndrome Cardiovascular Hypertension, coronary heart disease, congestive heart failure, dysrhythmia, pulmonary hypertension, ischemic stroke, venous stasis, deep venous thrombosis, pulmonary embolism, chronic kidney disease (CKD). Respiratory Abnormal pulmonary function, obstructive sleep apnoea, obesity hypoventilation syndrome Musculoskeletal Osteoarthritis, gout, low back pain Gynecologic Abnormal menses, infertility. Genitourinary Urinary stress incontinence. Ophthalmologic Cataracts Neurologic Idiopathic intracranial hypertension ( pseudo-tumor cerebri ). Cancers Esophagus, colon, gallbladder, cervix, breast, uterus, kidney, prostate. Postoperative events Atelectasis, Pneumonia, Deep venous thrombosis, pulmonary embolism.

21

2.7.0 MEASUREMENT OF OBESITY: Accurate assessment of body fat mass requires the use of sophisticated and expensive technologies that are not readily available to most physicians.

Moreover, the determination of healthy and unhealthy amounts of fat mass is complicated because the amount of body fat that causes medical complications depends on sex, age, fat distribution, weight (fat) gain since early adulthood, level of fitness, genetic factors, and concomitant disease risk factors.66

2.7.1 Body Mass Index: The Body mass index is commonly used to determine desirable body weight. Invented by a Belgian Polymath, Adolphe Quetelet, between 1830 and 1850, BMI is a measure of weight in relation to height and is calculated as weight (kg) divided by height (m2) squared.66 Although, BMI usually correlates closely with percent body fat mass in a curvilinear fashion, some persons with an “obese” BMI may have a normal amount of body fat and a large muscle mass, while others with a “normal” BMI may have excess adiposity and reduced muscle mass.

The World Health Organization, the National Institutes of Health (NIH), Healthy People 2010, and the 2000 Dietary Guidelines for Americans have all proposed similar guidelines for classifying weight status by body mass index (Table 2.7.1). People with a BMI of 18.5 to 24.9 kg/m2 are normal. While those with BMI of 25.0 to 29.9 kg/m2 are considered overweight and those with BMI of 30 kg/m2 and above are obese 66, 68, 69.

22

Table 2.7.1: Body Mass Index Associated Disease Risk

OBESITY CLASS BMI (kg/m2) RISK

UNDERWEIGHT <18.5 INCREASED

NORMAL 18.5-24.9 NORMAL

OVERWEIGHT 25.0-29.9 INCREASED

OBESITY I 30.0-34.9 HIGH

II 35.0-39.9 VERY HIGH

EXTREME OBESITY III ≥40.0 EXTREMELY HIGH

2.7.2 Waist Circumference and Waist-Hip Ratio:

The importance of fat distribution on health has also been well recognized. Compared with obese persons who have predominantly increased lower body fat (gluteal and femoral fat) phenotype, obese persons with excess upper body fat (abdominal fat) phenotype are at increased risk for diabetes, hypertension, dyslipidemia, and ischemic heart disease.28, 69 Measurement of abdominal fat content requires the use of expensive radiological imaging techniques, so waist circumference is often used as a surrogate marker because it has been shown to correlate closely with abdominal fat mass.70 The Expert Panel on the Identification, Evaluation, and Treatment of

Overweight and Obesity in Adults, convened by the National Institutes of Health, proposed that men with a waist circumference greater than 102 cm (40 inches) and women with a waist circumference greater than 88 cm (35inches) are at increased risk for metabolic diseases (Table

2.3 and 2.4).69

Therefore, abdominal obesity according to the report of the National Cholesterol Education

Program Adult Treatment Panel (ATP) III are WC ≥ 102 cm in men and WC ≥ 88 cm in

Women.28 Similarly, measurement of the ratio circumference of waist to hip (WHR) can be used

23 to determine abdominal obesity. According to the WHO, central obesity is defined as WHR >

0.85 for female and WHR > 0.9 for male.71

The WHO recommended protocol for measuring both waist and hip circumferences are as by a

WHO expert consultation committee.72 Waist circumference should be measured at the midpoint between the lower margin of the lowestst palpable rib and the top of the iliac crest, using a stretch‐resistant tape that provides a constant 100 g tension. Hip circumference should be measured around the widest portion of the buttocks, with the tape parallel to the floor. For both measurements, the subject should stand with feet close together, arms at the side and body weight evenly distributed, and should wear light clothing. The subject should be relaxed, and the measurements should be taken at the end of a normal expiration. Each measurement should be repeated twice; if the measurements are within 1 cm of one another, the average should be calculated. If the difference between the two measurements exceeds 1 cm, the two measurements should be repeated.72

24

TABLE 2.7.2: CLASSIFICATION OF OVERWEIGT AND OBESITY BY BMI, WAIST CIRCUMFERENCE AND ASSOCIATED DISEASE RISK DISEASE RISK* RELATIVE TO WEIGHT AND WAIST CIRCUMFERENCE Men ≤ 102cm ( ≤ 40 in) >102cm ( > 40 in)

BMI (kg/m2) OBESITY CLASS Women ≤ 88cm (≤ 35 in) >88cm ( > 35 in)

UNDERWEIGHT <18.5 -- --

NORMAL 18.5-24.9 -- --

OVERWEIGHT 25.0-29.9 INCREASED HIGH

OBESITY 30.0-34.9 I HIGH VERY HIGH

35.0-39.9 II VERY HIGH VERY HIGH

MORBID OBESITY ≥40.0 III EXTREMELY HIGH EXTREMELY HIGH

*Disease risk for type 2 diabetic, hypertension and cardiovascular diseases .

Table 2.7.3: Classification of abdominal obesity by waist circumference (cm).

Classification Males Females

Not overweight <94.0 <80.0

Overweight

Pre-obese 94.0 – 101.9 80.0 – 87.9

Obese ≥102.0 ≥88.0

25

2.7.3 OTHER MEASUREMENTS OF OBESITY

Apart from anthropometric measurements mentioned above, other useful measurements of obesity are by analysis of body fat composition (BFC) by various techniques which include; skin fold thickness measurements, radioisotope dilution methods, hydrodensitometry and underwater weighing, bioelectrical impedance analysis (BIA), air displacement plethysmography (ADP), dual energy X-rays absorptiometry (DEXA), computer tomography(CT) ,magnetic resonance imaging (MRI),and positron emission tomography (PET).73 Although, these techniques are not readily available and affordable for routine clinical practice, it is advised that

a BC measurement if possible should be included in obesity assessment and for this purpose measurements of skin fold thickness combined with BIA are quite sufficient for routine clinical practice.73 However, in specialized clinics and in research, more sophisticated methods like

ADP, DEXA, e.t.c., can be used. In obesity, assessment of BFC contributes to diagnosis and the pathological impact of visceral adipose tissue. In addition, conditions such as pseudo- or hypermuscular obesity and sarcopenia, which are often observed in various endocrine diseases, can be investigated in detail by assessment of BC using these techniques.73.

Skinfold Measurement: Generally speaking, skinfold measurement is easy to use, and inexpensive portable method. The equipment used for this assessment includes a skinfold caliper which is designed specifically for simple accurate measurement of subcutaneous tissue. Either a

7 or 3 site skinfold may be assessed.

7 site skinfold: chest, triceps, subscapular, axilla, suprailiac, abdomen, thigh

3 site skinfold (Men): chest, abdomen, thigh.

3 Site Skinfold (Women) : tricep, suprailiac, thigh

26

Commonly used calipers include Lange, Slim glide and Harpenden Skinfold Calipers. Skinfold measurement is made by grasping the skin and underlying tissue, shaking it to exclude any muscle and pinching it between the jaws of the caliper. These hand-held calipers exert a standard pressure and the skinfold thickness is measured at various body locations (3-7 test sites are common). Duplicate readings are often made at each site to improve the accuracy and reproducibility of the measurements. Then a calculation is used to derive a body fat percentage based on the sum of the measurements.74 The Percent body fat (%BF) can be calculated from body density using the Siri Equation as stated below;

%BF = [(4.95/body density) × 4.50] × 100.

The body density can be calculated using Jackson and Pollock’s body density equations which are different for males and females.75, 76

Body Density Equations: Jackson & Pollock

Males Equation 1:

2 Body Density = 1.0990750 - 0.0008209 (X2) + 0.0000026 (X2) - 0.0002017 (X3) - 0.005675

(X4) + 0.018586 (X5). Where X2 = sum of the chest, abdomen and thigh skinfolds in mm, X3 = age in years, X4 = waist circumference in cm, and X5 = forearm circumference in cm.

Equation 2:

Body Density = 1.10938 - (0.0008267 x sum of chest, abdomen and thigh skinfolds in mm ) +

(0.0000016 x square of the sum of chest, abdomen and thigh) - (0.0002574 x age)

27

Females Equation 1:

2 Body Density = 1. 1 470292 - 0.0009376 (X3) + 0.0000030 (X3) - 0.0001156 (X4) - 0.0005839

(X5), Where: X3 = sum of triceps, thigh and suprailiac skinfolds, in mm, X4 = age in years and X5

= gluteal circumference in cm.

Equation 2:

Body Density = 1.0994921 - (0.0009929 x sum of triceps, thigh and suprailiac skinfolds) +

(0.0000023 x square of the sum of triceps, thigh and suprailiac skinfolds) - (0.0001392 x age in years)

Bioelectrical impedance analysis (BIA): is a simple, portable technique that is very acceptable to patients and has high precision of measurement, and so may have a role in longitudinal monitoring of change in body composition. Bioelectrical impedance analysis, as a noninvasive and relatively inexpensive method, has been used for measurements of body composition parameters such as total body water (TBW), extracellular water (ECW),Fat free mass (FFM), which is the sum of lean body mass (LBM) and bone mineral content (BMC).

Impedance is mostly used for measuring body fluid volumes, FFM and fat tissue mass.77 BIA involves passage of a small alternate current (a.c.) electrical current through the body. The current is conducted by body water so impedance is inversely related to total body water

(TBW).74 Thus, the FFM they measure results from an extrapolation to the whole body using a proprietary equation of resistance, weight, height, age and sex obtained, in principle, by comparison with DEXA data. Their fat tissue mass is equal to the difference between body weight and FFM.77

28

2.8.0 PRINCIPLE OF MANAGEMENT OF OBESITY

The presence of overweight and obesity in a patient is of medical concern because it increases the risk for several diseases, particularly cardiovascular diseases (CVDs) and diabetes mellitus

and it also increases all-cause mortality. Treatment of the overweight and obese patient is a two- step process: assessment and management. Assessment requires determination of the degree of obesity and absolute risk status. Management includes both weight control or reducing excess body weight and maintaining that weight loss as well as instituting other measures to control associated risk factors.69

2.8.1 ASSESSMENT OF RISK STATUS

The patient’s risk status should be assessed by determining the degree of overweight or obesity based on BMI, the presence of abdominal obesity based on waist circumference, and the presence of concomitant CVD risk factors or comorbidities. Some obesity-associated diseases and risk factors place patients in a very high risk category for subsequent mortality. These diseases will require aggressive modification of risk factors in addition to their own clinical management. Other obesity-associated diseases are less lethal, but still require appropriate clinical therapy. Obesity also has an aggravating influence on several cardiovascular risk factors.

Identifying these risk factors is required as a guide to the intensity of clinical intervention. 69

A clinical staging system for obesity called Edmonton Obesity Staging System (EOSS) proposed by Sharma et al.,78 with recommended intervention measure for every stage can be used to assess the severity of obesity along with body mass index in a clinical setting in order to individualize management option for obesity.78

29

EOSS Components

STAGE 0: Patient has no apparent obesity-related risk factors (e.g., blood pressure, serum lipids, fasting glucose, etc. within normal range), no physical symptoms, no psychopathology, no functional limitations and/or impairment of well-being.

STAGE 1: Patient has obesity-related subclinical risk factor(s) (e.g., borderline hypertension, impaired fasting glucose, elevated liver enzymes, etc.), mild physical symptoms (e.g., dyspnea on moderate exertion, occasional aches and pains, fatigue, etc.), mild psychopathology, mild functional limitations and/or mild impairment of well being.

STAGE 2: Patient has established obesity-related chronic disease(s) (e.g., hypertension, type 2 diabetes, sleep apnea, osteoarthritis, reflux disease, polycystic ovary syndrome, anxiety disorder, etc.), moderate limitations in activities of daily living and/or well being.

STAGE 3: Patient has established end-organ damage such as myocardial infarction, heart failure, diabetic complications, incapacitating osteoarthritis, significant psychopathology, significant functional limitation(s) and/or impairment of well being.

STAGE 4: Patient has severe (potentially end-stage) disability/ies from obesity-related chronic diseases, severe disabling psychopathology, severe functional limitation(s) and/or severe impairment of well being.

30

A pragmatic approach to managing patients at the different stages of obesity: EOSS

Management options

For STAGE O: Identification of factors contributing to increased body weight. Counseling to prevent further weight gain through lifestyle measures including healthy eating and increased physical activity.

For STAGE 1: Investigation for other (non-weight related) contributors to risk factors. More intense lifestyle interventions, including diet and exercise to prevent further weight gain.

Monitoring of risk factors and health status.

For STAGE 2: Initiation of obesity treatments including considerations of all behavioral, pharmacological and surgical treatment options. Close monitoring and management of comorbidities as indicated.

For STAGE 3: More intensive obesity treatment including consideration of all behavioral, pharmacological and surgical treatment options. Aggressive management of comorbidities as indicated.

For STAGE 4: Aggressive obesity management as deemed feasible. Palliative measures including pain management, occupational therapy and psychosocial support.

31

2.8.2 MANAGEMENT OF OBESITY

The general goals of weight loss management are: (1) to reduce body weight; and (2) to maintain a lower body weight over the long term; or (3) at a minimum, to prevent further weight gain. Specific targets for each of these goals can be considered. The initial goal of weight loss therapy should be to reduce body weight by approximately 10 percent from baseline. With success, further weight loss can be attempted, if indicated, through further assessment. Weight loss should be about 1 to 2 lb (0.5 to1kg)/week for a period of 6 months, with the subsequent strategy based on the amount of weight lost.69

2.8.3 MANAGEMENT STRATEGIES

The conventional strategies of obesity management are kilojoule reduction and an increase in physical activity through various options including lifestyle strategies (diet and physical activity), behavioural and psychological interventions, pharmaceutical interventions and bariatric surgery.3, 69, 79

Dietary Therapy: Low-calorie diets are recommended for weight loss in overweight and obese persons. Reducing fat as part of a low-calorie diet is a practical way to reduce calories however, reducing dietary fat alone without reducing calories is not sufficient for weight loss. Reducing dietary fat, along with reducing dietary carbohydrates, can facilitate a more beneficial caloric reduction. Therefore, a diet that is individually planned to help create a deficit of 500 to 1,000 kcal/day should be an integral part of any program aimed at achieving a weight loss of 1 to 2 lb/week.69

Physical Activity: Physical activity is recommended as part of a comprehensive weight loss therapy and weight maintenance program because it: (1) modestly contributes to weight loss in overweight and obese adults, (2) may decrease abdominal fat , (3) increases cardiorespiratory

32 fitness, and (4) may help with maintenance of weight loss. Physical activity should be an integral part of weight loss therapy and weight maintenance. Initially, moderate levels of physical activity for 30 to 45 minutes, 3 to 5 days per week should be encouraged. All adults should set a long-term goal to accumulate at least 30 minutes or more of moderate intensity physical activity on most, and preferably all, days of the week. The combination of a reduced calorie diet and increased physical activity is recommended since it produces weight loss, decreases abdominal fat, and increases cardiorespiratory fitness.69

Behavioural and Psychological Therapy: This is a useful adjunct when incorporated into treatment for weight loss and weight maintenance. Practitioners need to assess the patient’s motivation to enter weight loss therapy; assess the readiness of the patient to implement the plan and then take appropriate steps to motivate the patient for treatment. Behavioural therapy strategies to promote diet and physical activity should be used routinely, as they are helpful in

69 achieving weight loss and weight maintenance.

Pharmacotherapy: Weight loss drugs approved by the FDA may be used as part of a comprehensive weight loss program including diet and physical activity for patients with a BMI of ≥ 30 with no concomitant obesity- related risk factors or diseases, and for patients with a BMI of ≥ 27 with concomitant obesity-related risk factors or diseases. Drugs should never be used without concomitant lifestyle modification. Continual assessment of drug therapy for efficacy and safety is necessary. If the drug is efficacious in helping the patient lose and/or maintain weight loss and there are no serious adverse effects, it can be continued. If not, it should be

69 discontinued. Prescription currently evaluated as antiobesity agents include:

33 bupropion SR, metformin, , , topiramate, , and low-dose orlistat.29.

A recent review article on pharmaceutical interventions for obesity by Caveney et al.80 Showed the following current and future antiobesity drugs as discussed below.

Current Anti-obesity Drugs

Amphetamine: This is a central adrenergic agonist which causes central noradrenaline release.

Its weight loss properties were first shown in 1938.It has a high abuse and addiction potential can also cause elevation of cardiac output and blood pressure. Therefore, it is very rarely used for obesity management.

Amphetamine derivatives: These include , , Diethylpropion, and . Mechanism of action is similar to that of amphetamine through central norepinephrine and dopamine release. They are approved only for short treatment periods of up to 12 weeks

Rimonabant: This is a selective cannabinoid receptor (CB1) antagonist. It was withdrawn from the market in 2009 because its use was found to be associated with severe psychiatric side effects, such as depression, anxiety and suicidal ideation.

Sibutramine: This is a serotonin and norepinephrine reuptake inhibitor which was approved as an antiobesity drug in 1997 US-FDA and recently withdrawn from market in 2010 due to its cardiovascular side effects.

Mazindol: This ia sympathomimetic amine initially approved as an anti-obesity drug in1973 by

US-FDA and later withdrawn from US market in 2001because of allegations of increased risk of cardiac valvulopathy with its use.

34

Fenfluramine: This is a serotonin reuptake inhibitor that can also cause serotonin release from vesicular storage. It was approved in1973 by US-FDA and withdrawn from the United States

1997and later from other countries after reports of valvular heart damage (caused by selective stimulation of 5-HT2B receptors on human cardiac valves) and primary pulmonary hypertension.

Phenylpropanolamine: This drug acts by causing central norepinephrine and epinephrine release. It was approved in1979 by US-FDA and withdrawn in 2000 because of increased risk of haemorrhagic stroke.

Dinitrophenol: This drug acts through the uncoupling of oxidative phosphorylation from the production of ATP, leading to calorie loss as heat. It was introduced in the United States in 1933 and withdrawn in 1938 because of cases of fatal hyperthermia, rashes and cataract.

Ephedra: This is also a sympathomimetic drug approved in 1947 and banned in 2004 by US-

FDA because of the associated increased risk of cardiovascular and neuropsychiatric adverse events with its use.

Orlistat (Xenical): This is a gastrointestinal lipase inhibitor that acts by inhibiting the absorption of dietary fat.

Lorcaserin (Arena): This is a selective 5-HT2C receptor agonist.

Qnexa (Vivus): This is a combination of phentermine and topiramate.

35

Future Anti-obesity Drugs

Drugs that are presently undergoing different phases of drug trial for future management of obesity include the following:

Contrave (Orexigen): This is a combination of naltrexone and bupropion.

Cetilistat (Norgina BV/Takeda): This is a pancreatic lipase inhibitor.

Empatic (Orexigen): It is a drug combination of bupropion and zonisamide.

Tesofensine (NeuroSearch): A triple reuptake inhibitor (serotonin, norepinephrine and dopamine).

Liraglutide (NovoNordisk): This is GLP-1 analogue already approved for type 2 diabetes mellitus and presently is is undergoing phase 3 studies for obesity.

Peptide YY (PYY), Pancreatic polypeptide (PP): These drugs include Obinepitide (Nastech),

TM30339 (Nastech) and PP1420 (Wellcome Trust). Obinepitide is a synthetic analogue of PYY and PP. TM30339 targets the PP Y4 receptor while PP1420 is a PP analogue.

Neuropeptide Y (NPY) modulator: Example include Velneperit which is a NPY Y5 receptor antagonist.

Melanin-concentrating hormone-1 receptors antagonists: An example is BMS-830216

(Bristol Myers Squibb).

Pramlintide plus : is a synthetic analogue of while metreleptin is an analogue of human leptin.

Agouti related peptide (AgRP) antagonists: An example is TTP435 (TransTech).

36

Beta-3 adrenergic receptor agonists: LY377604.

Methionine aminopeptidase 2 (MetAP2) inhibitor: ZGN-433 (Zafgen).

Sodium glucose transporter 2 (SGLT2) inhibitor: PF04971729 (Pfizer).

Diglyceride Acyltransferase1(DGAT1) inhibitor: PF-04620110 (Pfizer).

Dopamine (D3) receptor antagonists: GSK598809 (GSK).

Mu- antagonists: GSK1521498 (GSK).

Vabicaserin (Wyeth): This is an antipsychotic drug.

Other anti-obesity drugs in development are Melanocortin-4 receptor (MC4R) agonists and 5-

HT6 receptor ligands

Bariatric Surgery (Weight Loss Surgery) : Weight loss surgery is an option in carefully selected patients with clinically severe obesity (BMI ≥ 40 or ≥35 with comorbid conditions) when less invasive methods of weight loss have failed and the patient is at high risk for obesity-

69 associated morbidity or mortality. There are several types of weight loss procedures (bariatric surgery) that are categorized by their mechanism of action: Restrictive (e.g., Adjustable gastric banding), Malabsorptive (e.g., Bileopancreatic diversion), or a combination of Restrictive and

Malabsorptive peocedures (e.g., Roux-en-Y gastric bypass).29

37

CHAPTER THREE

3.0.0 SUBJECTS, MATERIALS AND METHODS

3.1.0 STUDY DESIGN: This was a cross-sectional comparative hospital based study

3.2.0 STUDY LOCATION: This study area was the Endocrinology, Diabetes and Metabolism

(EDM) Unit Out-patient’s Clinic of the Obafemi Awolowo University Teaching Hospitals’

Complex (OAUTHC), Ile-Ife, Osun State, which is situated in the southwest geopolitical zone of

Nigeria. The hospital is a 576 bed facility which offers tertiary healthcare services and serves as a referral centre for Osun state and her adjoining states of Oyo, Ondo, Ekiti, Kogi and Edo states.

The EDM unit of this hospital runs out-patient clinic consultations thrice weekly.

3.3.0 STUDY PERIOD: The study was conducted between January and June 2012.

3.4.0 STUDY POPULATION: These included obese and non-obese females with type 2 diabetes mellitus and age comparable obese apparently healthy female subjects.

3.5.0 SAMPLING METHOD: This was by a non-probability method. All consenting subjects who met the inclusion criteria for each of the 3 groups as stated below were recruited consecutively from the Endocrinology, Diabetes, and Metabolism Unit outpatient’s clinic,

General Outpatient Department (GOPD) clinic and staff clinic of OAUTHC until the calculated sample size was reached.

38

3.6.0 INCLUSION CRITERIA:

1. All obese female subjects with BMI ≥ 30kg/m2 each and all non-obese female subjects

with BMI < 30 kg/m2.

2. Obese and non-obese females with type 2 diabetes mellitus diagnosed based on the

WHO criteria of 1998.71

3. Apparently healthy obese non-diabetic female Nigerians with fasting plasma glucose

(FPG) less than 6.1 mmol/l as defined by WHO criteria of 1998.71

4. Adult females aged between 20 years and 64 years based on the age range mostly

affected by diabetes.81, 82

3.7.0 EXCLUSION CRITERIA:

1. Subjects who were unwilling to participate in the study.

2. Pregnant women.

3. Acute febrile illness in the week preceding commencement of the study and subjects

presenting with diabetic emergencies.

4. Subjects who were known or suspected to have chronic debilitating diseases such as

chronic heart failure, chronic liver disease, chronic renal failure, chronic obstructive

pulmonary disease, sickle cell diseases, anaemia, tuberculosis, retroviral disease and

malignancy.

5. Subjects who were known or suspected to have other endocrine diseases related to

diabetes mellitus or obesity such as Cushing’s syndrome, hypothyroidism, polycystic

ovarian syndrome, acromegaly , e.t.c.

6. Subjects who were on long tern steroid use or currently on steroid therapy.

39

3.8.0 SAMPLE SIZE DETERMINATION:

The sample size was calculated for the initial study proposal compring only two groups using the sample size equation for a study comparing two means as stated below.83, 84

2 2 N= 4σ (Zcrit + Zpwr) D2 Where N = the total sample size (the sum of the sizes of both comparison groups)

σ = The assumed SD of each group (assumed to be equal for both groups)

zcrit = The standard normal deviation value that is given for the desired significance criterion which is 1.960 for the selected significance criteria of 0.05 (95% confidence level) that was used for this study zpwr = The standard normal deviation value that is given for the desired statistical powers which is 0.842 for the statistical power of 0.80 that was used for this study

D = The minimum expected difference between the two means

On the basis of the results of a previous study which showed the means and standard deviations of the serum leptin concentrations for obese women with and without type 2 diabetes,58 the equation above gave the value of N to be 101.2.

This calculated total sample size was increased by 10% in order to accommodate for attrition.

Therefore, N became 111.32 which was rounded off to 112. However, the total sample size was increased to 180 which now covered 3 groups of subjects as follows:

A) 60 Obese type 2 diabetic females,

B) 60 Obese non-diabetic female,

C) 60 Non-obese females with type 2 diabetes mellitus.

40

3.9.0 MATERIALS: EQUIPMENTS AND REAGENTS

3.9.1 EQUIPMENTS:

1.Mercury Sphygmomanometer (Accoson brand, England)

2.Littman Classic II Stethoscope (Littman Quality TM, USA)

3.SECA weighing scale, England

4.SECA stadiometer, England

5.Flexible non stretch measuring tape

6.Accu-check active Glucometer and test strips.( Roche diagnostics, Germany)

7.Spectrophotometer ( Spectro SC2OD) Labomod Inc England.

8.Glycosylated Haemoglobin Auto-Analyzer (in2itTM A1c Bio-Rad Laboratories)

9.URIT 8020 Chemistry Auto-Analyzer (URIT Medical Electronic Co,. Ltd, China)

10.ELISA Machine for Leptin and Insulin Assay: (Chemwell 2910 Auto-Analyser [Awareness

Technology Incorporated, USA]).

General laboratory equipment including, centrifuge, test tubes, pipettes, sample trays, plain specimen bottles, fluoride oxalate specimen bottles, lithium heparin specimen bottles, EDTA specimen bottles,5ml and 10ml syringes with 21G needles.

3.9.2 REAGENTS:

1.RANDOX Glucose oxidase preparation from RANDOX Laboratories Ltd., UK.

2.RANDOX Lipid profile test kits from RANDOX Laboratories Ltd., UK.

3. Insulin ELISA test kits (Cusabio Biotech Co. Ltd, USA)

4. Human Serum Leptin Sandwich ELISA test kits (by Diagnostic Automation, Inc., USA)

41

3.10.0 DATA COLLECTION METHOD: This was by quantitative research method using clinical records, clinical observation including physical examination and laboratory tests.

3.11.0 DATA COLLECTION AND COLLATION: Subjects that met the inclusion criteria were recruited into the study after written informed consent had been obtained from them. Each subject was interviewed using a data proforma (Appendix 1). Demographic data and clinical history were obtained by interviewing the study subjects and also from information in their hospital case folders. Physical examination was performed on each subject to exclude those with physical findings in keeping with the exclusion criteria. Body weight, height, body mass index

(BMI), waist circumference (WC), hip circumference (HC), waist to hip ratio (WHR) and blood pressure were measured in all study subjects and recorded.

All non-diabetic obese subjects had initial fasting plasma glucose (FPG) screening test done with

Accu-check active glucometer in order to aid in the selection of subjects with normoglycaemia alone. Laboratory assessment for all subjects included the collection of 20 mls of venous blood sample under aseptic procedure from the cubital fossa of each subject between 8.00 and 8.30 a.m after an overnight fast of at least 8 hours but not more than 12 hours. These samples were then divided in aliquot into the following specimen bottles consisting; fluoride oxalate bottle, ethylene-diamine-tetra-acetic acid (EDTA) bottle, lithium heparin bottle and a plain specimen bottle respectively and kept in aliquots till ready for analysis.

The samples in the fluoride oxalate bottles were used for analysis of plasma glucose, those samples in the EDTA bottles were used for glycosylated haemoglobin levels (HBA1c) while the samples in the lithium heparin bottles were used for analysis of lipid parameters (total cholesterol, high density cholesterol, low density cholesterol and triglyceride).The samples in the plain specimen bottle were allowed to clot and thereafter were centrifuged at 3000 revolution per

42 minute for five minute to extract the serum into another set of plain specimen bottles which were then stored frozen at -20oC till ready for analysis and measurement of fasting serum insulin and fasting serum leptin.

HbA1C was measured in subjects with type 2 diabetes as an index of glycaemic control. Based on

HbA1C results, type 2 diabetic subjects were then categorized as controlled or non-controlled. All subjects were assessed for insulin resistance using the homeostasis model assessment of insulin resistance (HOMA-IR) as described by Matthews et al.85, 86

3.11.1 MEASUREMENT OF CLINICAL AND ANTHROPOMETRIC PARAMETERS

Weight: Body weight was measured with subjects in light clothing and shoes off to the nearest

0.1 kilogram (Kg) using a standardized weighing scale (Seca weighing scale) placed on an even horizontal hard surface.

Height: Height in metres (m) were measured in subjects without wearing head gear and shoes in erect position against a graduated height scale (Seca stadiometer) to the nearest 0.5 centimetres

(cm). Subject stood with both feet flat on the platform at the base of the stadiometer with both heels together and touching the vertical and toes apart pointing outward at about angle 60 degree.

The arms by the side with shoulders relaxed, buttocks, upper back and back of the head touching the vertical.

Head was oriented in Frankfort horizontal plane with the subject looking straight at a distant object. The head is in the Frankfort horizontal plane when the horizontal line from the ear canal to the lower border of the orbit of the eye is parallel to the floor platform and perpendicular to the vertical backboard. Subject was then asked to take a deep breath in and hold his/her breath at maximum inspiration while the height was measured against the vertical at the level of vertex.

43

Body Mass Index (BMI): Body mass index (kg/m2) was calculated as the weight of subject in kilogram divided by square height of the same subject in metres and recorded in kilogram per square meter (Kg/m2).68

.Waist Circumference (WC): This was measured to the nearest 0.1 cm using a flexible non stretch measuring tape at a point half way between the lower margin of the lowest palpable rib and the top of iliac crest with the tape parallel to the floor. The subject stood in relaxed position with feet close together, arms at the side and body weight evenly distributed and the measurements were taken at the end of a normal expiration. Each measurement was repeated; if the measurements were within 1 cm of one another, the average was calculated.72

Hip Circumference (HC): This was measured to the nearest 0.1 cm using a flexible non stretch measuring tape at a point around the widest portion of the buttocks ( point of maximum extension of the buttock) with the tape parallel to the floor. The subject stood in relaxed position with feet apposed together, arms at the side and body weight evenly distributed. Each measurement was repeated; if the measurements were within 1 cm of one another, the average was then calculated.72

Waist to Hip Ratio (WHR): This was calculated by dividing the measured waist circumference of a subject by the measured hip circumference of the same subject.

Blood Pressure (BP): Brachial blood pressure measurements were taken by auscultatory method using standard mercury sphygmomanometer with appropriate cuff size (cuff bladder encircling at least 80 percent of the arm) for all subjects after five minutes rest in a sitting and a relaxed position. All measurements were taken to the nearest 2.0 millimeters of mercury from the right arm which was positioned at the level of the heart of the subject. Systolic BP was recorded at phase 1 Korotkoff sound while diastolic BP was recorded at phase 5 korotkoff sound. The

44 average of two BP measurements taken at least one minute interval were calculated and recorded for subjects according to JNC VII classification87 as shown below.

Normal Less than 120/80 mmHg

Pre hypertension 120-139/80-89mmHg

Stage1 hypertension 140-159/90-99mmHg

Stage 2 hypertension Greater or equal to 160/100mmHg

3.11.2 LABORATORY MEASUREMENTS

FASTING PLASM GLUCOSE: This was measured with the spectrophotometer with the aid of glucose oxidase preparation supplied by RANDOX Laboratory Ltd., United Kingdom using the principle of Trinder reaction as described below (Appendix 5).

Enzymatic indicator test based on the Trinder reaction quantified by the formation of a pink quinoneimmine dye. In this reaction plasma glucose is determined after enzymatic oxidation in presence of glucose oxidase (GOD). The hydrogen peroxide formed is catalyzed by peroxidase

(POD) and reacts with phenol and 4-aminoantipyrine to form the dye indicator.88 The absorbance of the dye indicator formed were the measured by the spectrophotometer to determine the plasma glucose levels.

GOD Glucose + O2 + H2O Gluconic acid + H2O2

POD H2O2 + 4-aminoantipyrine + phenol Quinoneimine + H2O2

45

GLYCOSYLATED HAEMOGLOBIN: This was measured from the venous blood samples by a principle based on boronate affinity chromatography with the aid of the Biorad in-2-it glycosylated haemoglobin autoanalyser and test catridges after the initial standardization of the autoanylyser with a system check cartridge (Appendix 6).

FASTING LIPID PROFILE: Total Cholesterol, Low Density Lipoprotein-Cholesterol, High

Density Lipoprotein-Cholesterol and Triglyceride were measured from the plasma samples by spectroscopy technique using URIT 8020 Chemistry Auto-Analyzer (URIT Medical Electronic

Co., Ltd., China) with RANDOX Lipid test kits from RANDOX Laboratories Ltd., UK

(appendix 7).

FASTING SERUM LEPTIN: This was measured by double assay from the sera of subjects as total serum leptin. This quantitative estimation of human serum leptin assay was done using the

Human leptin kit with batch number 1242-6 (supplied by Diagnostic Automation, Inc, Calabasas,

CA 91302USA.) using a Chemwell 2910 miceowll ELISA immunoo-analyser (Appendix 8).

Assay sensitivity: 0.3ng/ml

Specificity of Antibodies (Cross Reactivity) for human insulin: 100%

Intra assay coefficient of variation (CV): 6.42%)

Inter assay coefficient of variation (CV): 10.11%

The expected values for a normal weight male = 3.84 ± 1.79ng/ml and for a normal weight female = 7.36 ± 3.73ng/ml.

FASTING SERUM INSULIN: Double assay for serum insulin by a quantitative method with microwell enzyme linked immunosorbent assay (ELISA) human insulin test kits (supplied by

Cusabio Biotech Co Ltd.,USA) were performed by Chemwell 2910 Auto-analyser (Appendix

9). The expected reference values for normal adults range from 0.7 to 9.0 µIU/ml and values for

46 adults with type 2 diabetes mellitus range from 0.7 to 25 µIU/ml. The sensitivity of this assay was 0.75µIU/ml and the test has no cross reactivity with C-peptide, proinsulin and glucagon. The intra assay coefficient of variation (CV) was 6.0%, while the inter assay coefficient of variation

(CV) was 7.4%

INSULIN RESISTANCE (HOMA-IR): The homeostasis model assessment of insulin resistance (HOMA-IR) was used to estimate insulin resistance as stated in the formula below.

HOMA-IR= Fasting Glucose (mmol/l) x Fasting Insulin (µIU/ml) / 22.5 as described by

Matthews et al.85, 86

3.11.3 DEFINITION OF TERMS

1. Obesity was defined as BMI ≥ 30 Kg/m 2 while non-obese was defined as BMI < 30

Kg/m2 and Central Obesity was defined as Waist Circumference (WC) ≥ 88cm or Waist

to Hip Circumference Ratio (WHR) ≥ 0.85 for females.28, 68, 71

2. Type 2 diabetic subjects were defined as all previously diagnosed diabetic subjects based

on the WHO classification and diagnostic criteria71 who are currently on oral

hypoglycaemic agents and or dietary therapy but not on insulin treatment.

3. Controlled diabetic subjects were taken as subjects with HbA1C < 7.0% while the Non-

controlled diabetic subjects were subjects with HbA1C ≥ 7.0%.

4. HOMA-IR cut off level of ≥ 2 was used to define individuals with insulin resistance as

previously described by Oli et al.,89 for Nigerians.

47

3.11.4 DATA ANALYSIS: This was done using Statistical Package for Social Sciences (SPSS) version 17.0 (SPSS Inc. Chicago Illinois). Except where otherwise stated, results were expressed as mean ± standard deviation (SD) and number count (N) with proportions (%). Descriptive analyses were presented with frequency tables and charts as appropriate.

Continous variables were compared among the three groups with Analysis of Variance

(ANOVA).Thereafter, post –hoc test were carried out on the result of ANOVA tables generated to identify the two groups with a statistically significant difference. Relationship between the serum leptin levels and diabetic control of obese and non-obese type 2 diabetic subjects was determined using Student T-Test while correlation using Spearman’s correlation coeficient was used on continuous variables. Classification of diabetes control between the obese and non-obese type 2 diabetic subjects groups and other categorical variables were also compared among the groups using Chi-square test with level of statistical significance set as p ≤ 0.05.

3.11.5 ETHICAL CONSIDERATION: Ethical approval was obtained from the Ethics and

Research Committee of OAUTHC (appendix 4). In addition, signed informed consent form was obtained from each subject after a discussion session explaining the required procedure to each subject in her best understood language (Appendices 2 and 3).

48

CHAPTER FOUR

4.0 RESULTS

4.1 Socio-Demographic Characteristics of the Study Population

One hundred and eighty females participated in the study comprising 60 subjects in each of the 3 groups: (a) Obese Type 2 DM, (b) Obese non-diabetic females and (c) Non-obese Type 2 DM.

The age range for all subjects was 34 to 64 years with their mean age being 52.0 ± 7.3 years.

Most of the subjects were married women 148 (82.2%) and majority 159 (88.3%) were

Christian. There were 173 (96.1%) subjects from the Yoruba ethnic group and most of the subjects were multipara 176 (97.8%) and 122 (67.8%) were postmenopausal women.

Only 19 (10.6%) subjects had no formal education, 50 (27.8%) had primary school education, 38

(21.1) had secondary school education, 38 (21.1%) had post-secondary school education other than university and 35 (19.4%) had university education. The educational attainments were comparable in all the three subject groups with no significant difference ( X2 = 15.421, df = 8, p

= 0.51) as shown in Figure 4.1. The two most common occupations of subjects were trading 80

(44.4%) and teaching 40 (22.2%). None of the subjects within the groups had history of smoking, alcohol use was also minimal and did not differ significantly among the groups as shown in Table 4.1.

49

Figure 4.1: Educational attainment of subjects in each group. X2 =15.421, df = 8, p = 0.51

50

Table 4.1: Comparison of social habit of the study participants

Parameter Obese T2DM Obese Non- Non-Obese P value DM T2DM

Age (Years) 52.8 ± 7.3 50.7 ± 7.3 52.6 ± 7.4 0.224

Alcohol use 1 (1.7%) 1 (1.7%) 2 (3.3%) 0.774

Smoking history 0 (0.0%) 0 (0.0%) 0 (0.0%) 0.366

DM = Diabetes Mellitus, T2DM = Type 2 DM, *P value < 0.05 is statistically significant

51

4.2 Comparison of clinical parameters of the study participants

The mean age ± SD of the Obese Type 2 DM group, Obese non-diabetic females group and the

Non-obese Type 2 DM group were 52.8 ± 7.3 years, 50.7 ± 7.3 years and 52.6 ± 7.4 years respectively. The mean age was comparable in all the three groups (F = 1.509, df = 2, p = 0.224).

Table 4.2 shows the comparison of the medical histories among the three groups. The histories of hypertension, anti-lipid drug use, family history of DM, family history of obesity and the childhood histories of obesity differed significantly among the groups. There was a family history of obesity in 50 (83.3%) of the Obese Type 2 DM subjects, 45 (75.0%) of the Obese non- diabetic subjects and 25 (41.7%) of the Non-obese Type 2 DM subjects. The proportion of subjects with family history of hypertension was similar in all subject groups. The mean duration of DM (3.8 ± 3.3 years) in the Obese Type 2 DM subjects was significantly lower than the mean duration (5.5 ± 4.3 years) in the Non-obese Type 2 DM subjects ( t = -2.420, df = 111.166, p =

0.017).

52

Table 4.2: Comparison of clinical parameters of the study participants

Parameter Obese T2DM Obese Non- Non-Obese P value DM T2DM

Age (Years) 52.8 ± 7.3 50.7 ± 7.3 52.6 ± 7.4 0.224

Family history of 25 (41.7%) 17 (28.3%) 16 (26.7%) 0.036* DM Family history of 28 (46.7%) 21 (35.0%) 22 (36.7%) 0.286 HTN Family history of 50 (83.3%) 45 (75.0%) 25 (41.7%) 0.001* obesity Childhood history of 27 (45.0%) 27 (45.0%) 14 (23.3%) 0.001* obesity Known HTN 46 (76.7%) 21 (35.0%) 38 (63.3%) 0.0001*

Antilipid drug use 19 (31.7%) 0 (0.0%) 13 (21.7%) 0.0001*

DM Duration 3.8 ± 3.3 NA 5.5 ± 4.3 0.017* (Years)

HTN = Hypertension, DM = Diabetes Mellitus, T2DM = Type 2 DM, NA= Not Applicable, *P value < 0.05 is statistically significant

53

4.3: Comparison of the anthropometric parameters of the study participants

Table 4.3 shows the values of the anthropometric parameters used to assess obesity. The three groups were significantly different in the values of their waist circumference, hip circumference, waist to hip circumference ratio, body weight and body mass index but not in the values of their height. The BMI ranges of the Obese Type 2 DM group, Obese non-diabetic females group and the Non-obese Type 2 DM group were 30.0 to 46.0 Kg/m2, 30.0 to 52.3 Kg/m2 and 19.7 to 29.3

Kg/m2 respectively. In accordance to BMI grading by WHO, obesity class I, class II and Class

III were present in 41 (68.3%), 15 (25.0%) and 4 (6.7%) of the Obese Type 2 DM subjects.

Among the Obese non-diabetic subjects, 27 (45.0%) had class I obesity, 18 (30.0%) had class II obesity and 15 (25.0%) had class III obesity. The Non-obese Type 2 DM group had 21 (35.0%) subjects with normal weight and 39 (65.0%) subjects who were overweight. The waist circumference (WC) ranges of the Obese Type 2 DM group, Obese non-diabetic females group and the Non-obese Type 2 DM group were 93.0 to127.0 cm, 85.0 to 129.0 cm and 76.0 to 106.0 cm respectively. Central obesity as defined by WC of at least 88 cm was present in all the Obese

Type 2 DM subjects, 59 (98.3 %) of the Obese non-diabetic subjects and in 43 (71.7%) of the

Non-obese Type 2 DM subjects.

54

Table 4.3: Comparison of the anthropometric parameters of the study participants

Parameter Obese T2DM Obese Non- Non-Obese P value P value (a) DM (b) T2DM (c) (aVbVc) (aVb)

Ht (cm) 157.2 ± 5.1 157.6 ± 10.6 160.3 ± 5.5 0.540 0.963

Wt (Kg) 85.6 ± 10.1 92.1 ± 14.0 66.1 ± 7.6 0.0001* 0.014*

BMI (Kg/m2) 34.5 ± 3.4 36.5 ± 5.1 25.9 ± 2.3 0.0001* 0.044*

WC (cm) 106.3 ± 7.5 105.6 ± 10.4 91.3 ± 6.4 0.0001* 0.969

HC (cm) 113.7 ± 8.9 119.9 ± 10.4 97.9 ± 5.5 0.0001* 0.003*

WHR 0.94 ± 0.06 0.88 ± 0.06 0.93 ± 0.05 0.0001* 0.0001*

WC= Waist Circumference, HC = Hip Circumference, Ht = Height, Wt = Weight, WHR = Waist to Hip Circuference Ratio, BMI = Body Mass Index *P value < 0.05 is statistically significant

55

4.4: Comparison of the blood pressure measurements of the study participants

Table 4.4 shows the mean and standard deviation of blood pressure measurements of the study population. The three groups had similar mean systolic BP and diastolic BP. The systolic BP ranges of the Obese Type 2 DM group, Obese non-diabetic females group and the Non-obese

Type 2 DM group were 100 to 200 mmHg , 100 to 170 mmHg and 94 to 210 mm respectively.

Also the diastolic BP ranges of the Obese Type 2 DM group, Obese non-diabetic females group and the Non-obese Type 2 DM group were 60 to 110 mmHg, 60 to 120 mmHg and 60 to 120 mmHg respectively.

56

Table 4.4: Comparison of blood pressure measurement and hypertension staging among the study participants

Parameter Obese T2DM Obese Non- Non-Obese P value P value (a) DM (b) T2DM (c) (aVbVc) (aVb)

Systolic BP (mmHg) 133.3 ±19.2 124.8 ± 18.7 130.2 ± 21.2 0.51 0.068

Diastolic BP 79.2 ± 11.1 78.3 ± 11.8 78.7 ± 10.8 0.908 0.900 (mmHg) Normal BP 11 (18.3%) 19 (31.7%) 13 (21.7%) Staging

Prehypertension 23 (38.3%) 24 (40.0%) 26 (43.3%)

Stage 1 19 (31.7%) 11 (18.3%) 13 (21.7%) Hypertension Stage 2 7 (11.7%) 6 (10.0%) 8 (13.3%) Hypertension BP = Blood Pressure, * P value < 0.05 is statistically significant.

57

Table 4.5: Comparison of the biochemical parameters of the study participants

Parameter Obese T2DM Obese Non- Non-Obese P value P value (a) DM (b) T2DM (c) (aVb) (aVbVc)

Fasting plasma glucose 8.1 ± 2.9 5.4 ± 0.5 8.3 ± 2.9 0.0001* 0.0001* (mmol/l)

HbA1C (%) 8.3 ± 2.9 NA 8.7 ± 3.0 NA 0.457

High density lipoprotein 1.2 ± 0.3 1.2 ± 0.3 1.3 ± 0.3 1.000 0.339 cholesterol (mmol/l)

Low density lipoprotein 3.4 ± 0.9 3.1 ± 0.8 3.2 ± 1.0 0.447 0.462 cholesterol (mmol/l)

Total cholesterol 5.4 ± 0.9 5.1 ± 0.8 5.2 ± 1.0 0.363 0.387 (mmol/l)

Triglyceride (mmol/l) 1.6 ± 0.4 1.6 ± 0.5 1.5 ± 0.4 0.959 0.244

Serum leptin (ng/ml) 20.61 ± 15.13 20.94 ± 17.64 7.59 ± 3.39 0.999 0.0001*

Serum Insulin (µIU/ml) 23.19 ± 19.54 20.67 ± 20.24 7.51 ± 3.84 0.866 0.0001*

HOMA-IR 8.11 ± 7.41 5.07 ± 5.25 2.76 ± 1.77 0.032* 0.0001*

Prevalence of IR (N/%) 60 (100.0%) 59 (98.3%) 40 (66.7%)

HbA1C = Glycosylated haemoglobin, HOMA-IR = Homeostasis model of assessment of insulin resistance. * P value < 0.05 is statistically significant, NA = Not Applicable, IR = Insulin Resistance

58

4.5 Comparison of biochemical parameters between the obese type 2 diabetic and obese

non-diabetic female subjects

Table 4.5 shows the comparison of the mean of biochemical parameters between the Obese type

2 diabetic and Obese non-diabetic female subjects a. The mean serum leptin levels (20.61 ±

15.13 ng/ml) in the Obese Type 2 DM subjects compared to the levels (20.94 ± 17.64 ng/ml) in the Obese non-diabetic females did not differ significantly (p =0.999). Similarly, there was no statistically significant difference in the mean serum levels of insulin (23.19 ± 19.54 µIU/ml) in

Obese Type 2 DM compared to the levels (20.67 ± 20.24µIU/ml) in Obese non-diabetic subjects

(p = 0.67). The HOMA-IR level (8.11 ± 7.41) in the Obese Type 2 DM subjects was significantly higher than the level (5.07 ± 5.25) in the Obese non-diabetic females subjects (p =

0.032)

4.6: Comparison of the biochemical parameters of all subjects

Table 4.5 also shows the comparison of the mean of biochemical parameters among the three groups. The levels of their HDL-Cholesterol (p = 0.339), LDL-Cholesterol (p = 0.4620), Total-

Cholesterol (P = 0.387) and Triglyceride (P = 0.244) showed no statistically significant differences between groups. The mean serum levels of leptin (F=18.902, df = 2, p= 0.0001), insulin (F =15.838, df = 2, p = 0.0001 and HOMA-IR (F= 15.143,df = 2, p =0.0001) differed significantly among the groups.

59

Figure 4.2 Mean serum leptin levels in the groups of study participants

The mean serum leptin levels in Obese Type 2 DM, Obese non-diabetic and Non-obese Type 2

DM subjects were 20.61 ± 15.13(95% CI = 16.70-24.52), 20.94 ± 17.64 (95% CI = 16.38-25.50) and 7.59 ± 3.39 (95% CI = 6.72-8.47) ng/ml respectively as shown in figure 4.2.

60

Figure 4.3 Mean serum insulin levels in the groups of study participants

The mean serum insulin levels in Obese Type 2 DM, Obese non-diabetic females and Non-obese

Type 2 DM subjects were 23.19 ± 19.54 (95% CI =18.14-28.24), 20.67 ± 20.24 (95% CI =

15.44-25.90) and 7.51 ± 3.84 (95% CI = 6.51-8.50) µIU/ml respectively as shown in figure 4.3.

61

The mean levels of HOMA-IR in Obese Type 2 DM, Obese non-diabetic females and Non-obese

Type 2 DM subjects were also 8.11 ± 7.41 (95% CI = 6.20-10.03), 5.07 ± 5.25 (95% CI = 3.71-

6.42) and 2.76 ± 1.77 (95% CI = 2.31-3.22) respectively. The prevalence of insulin resistance in each group as defined by HOMA-IR cut off level of ≥ 2 was 100.0% among the obese T2DM subjects, 98.3% among the obese non-diabetic subjects while it was 66.7% among the non-obese

T2DM subjects.

62

Table 4.6: Relationship of Serum Leptin Levels with BMI, WC, Serum Insulin Levels,

HOMA-IR, and HbA1C by Group.

Obese T2DM Obese Non-DM Non-Obese

T2DM

Parameter r-value p- r-value p- r- p-

value value value value

BMI +0.038 0.776 +0.281* 0.030 +0.039 0.769

WC -0.025 0.849 +0.237 0.068 +0.058 0.660

Serum insulin -0.077 0.558 +0.446* 0.0001 +0.030 0.821

HOMA-IR -0.293* 0.023 +0.385* 0.002 0.000 0.996

HbA1C -0.255* 0.049 NA NA -0.170 0.195

BMI = Body Mass Index, WC= Waist Circumference, r = Spearman’s simple correlation coefficient,

*p < 0.05 is statistically significant, NA = Not Applicable.

63

4.7 Relationship of Serum Leptin Levels with BMI, WC, Serum Insulin Levels, HOMA-

IR, and HbA1C by Group.

Table 4.6 shows the correlation coefficients of relationship between serum leptin levels and

BMI, WC, serum insulin levels, HOMA-IR, and HbA1C by group. In the Obese Type 2 DM subjects, serum leptin levels were not significantly correlated with BMI, WC, and serum insulin levels but were significantly and negatively correlated with HOMA-IR and HbA1C. In the Obese non-diabetic subjects, serum leptin levels were significantly and positively correlated with BMI, serum insulin and HOMA-IR but were not significantly correlated with WC. In the Non-obese

Type 2 DM subjects, there were no significant correlations between serum leptin levels and BMI,

WC, serum insulin levels, HOMA-IR, and HbA1C.

64

Table 4.7: Relationship of HOMA-IR with BMI, WC, Serum Insulin levels, and HbA1C by

Group.

Obese T2DM Obese Non-DM Non-Obese

T2DM

Parameter r-value p- r-value p- r-value p-

value value value

BMI -0.105 0.424 +0.432* 0.001 -0.011 0.932

WC +0.008 0.951 +0.454* 0.0001 -0.007 0.956

Serum insulin +0.483* 0.0001 +0.385* 0.002 +0.279* 0.031

HbA1C +0.196 0.134 NA NA +0.163 0.214

r = Spearman’s simple correlation coefficient, *p < 0.05 is statistically significant, NA = Not Applicable

65

4.8 Relationship of HOMA-IR with BMI, WC, Serum Insulin Levels, and HbA1C by Group.

Table 4.7 shows the correlation coefficients between HOMA-IR and BMI, WC, serum insulin levels, and HbA1C by Group. In the Obese Type 2 DM subjects, HOMA-IR was not significantly correlated with BMI, WC, and HbA1C but was significantly and positively correlated with serum insulin levels. In the Obese non-diabetic subjects, HOMA-IR was still significantly and positively correlated with BMI, WC, and serum insulin level. Furthermore, in the Non-obese

Type 2 DM subjects, there was no significant correlation between HOMA-IR and BMI, WC, and

HbA1C, except for its significant positive correlation with serum insulin levels.

66

Table 4.8: Classification of diabetes control among diabetic subjects.

Parameters Controlled DM Non-Controlled DM n (%) = 48 (40%) n (%) = 72 (60%)

HbA1C (%) 5.9 ± 0.7 10.2 ± 2.4

Obese T2DM 25 (41.7%) 35 (58.3%)

Non-Obese T2DM 23 (38.3%) 37 (61.7%) T2DM = Type 2 Diabetes Mellitus, n = number of subjects,

67

4.9 Relationship between serum leptin levels and glycaemic control in subjects with type 2

diabetes mellitus

Table 4.8 and 4.9 show the classification diabetes control and comparison of biochemical parameters between obese subjects with controlled and non-controlled diabetes. The total number of the diabetic subjects in the study was 120. Forty-eight (40%) diabetic subjects were assessed to have controlled diabetes (HbA1c < 7%) with a mean HbA1C of 5.09 ± 0.7% while 72

(60%) diabetic subjects had non-controlled diabetes (HbA1C ≥ 7%) with a mean HbA1C of 10.2 ±

2.4%. Among the Obese Type 2 DM subject group, 25 (41.7%) had controlled diabetes with a mean HbA1C of 5.9 ± 0.8% while 35 (58.3%) were uncontrolled diabetes with a mean HbA1C of

10.0 ± 2.4%. Among the Non-obese Type 2 DM subject group, 23 (38.3%) werecontrolled diabetes with a mean HbA1C of 5.9 ± 0.7% while 37(61.7%) were uncontrolled diabetes with a mean HbA1C of 10.4 ± 2.4% as shown in table 4.11. There was no statistically significant difference in the proportion of subjects with diabetic control in both groups (X2 =1.39, p =

0.709).

68

Table 4.9: Comparison of biochemical parameters between obese T2DM subjects with

controlled and non-controlled diabetes.

Parameters Controlled DM Non-Controlled DM P-value n (%) = 25 (41.7%) n (%) = 35 (58.3%)

HbA1C (%) 5.9 ± 0.8 10.0 ± 2.4 0.0001*

Serum leptin (ng/ml) 25.81 ± 21.00 16.90 ± 7.26 0.051

Serum Insulin 24.61 ± 21.20 20.90 ± 18.22 0.284 (µIU/ml) HOMA-IR 7.80 ± 6.28 8.33 ± 8.20 0.788

DM = Diabetes Mellitus, *P < 0.05 is statistically significant

69

Table 4.10: Correlation between Serum Leptin Levels and HbAIC in subjects with

controlled and non-controlled diabetes.

Controlled Diabetes Non-Controlled

Subjects Diabetes

r-value p-value r-value p-value

Obese T2DM +0.052 0.806 -0.238 0.168

Non-Obese T2DM -0.096 0.662 -0.202 0.231

T2DM= Type 2 diabetes mellitus, r = Spearman’s simple correlation coefficient, *p < 0.05 is statistically significant

70

4.10: Relationship between serum leptin levels and glycaemic control in obese type 2

diabetic subjects

Table 4.9 shows the comparison of the mean levels of biochemical parameters between obese

T2DM subjects with controlled and those with non-controlled diabetes. The mean serum leptin levels (25.81 ± 21.00 ng/ml) of the obese diabetic subjects with controlled diabetes was higher than the mean level (16.90 ± 7.26 ng/ml) in those with non –controlled diabetes but this was not statistically significant (t = 2.040, df = 28.143, p = 0.051). Similarly, there was no significant correlation between the serum leptin levels and HbA1C in the obese diabetic subjects with controlled diabetes (r = 0.052, p = 0.806) and also in the obese diabetic subjects with non- controlled diabetes (r = -0.238. p = 0.168) as previously shown in Table 4.10.

The mean serum insulin levels (24.61 ± 21.20 µIU/ml) of the obese diabetic subjects with controlled diabetes was also higher than the mean level (20.90 ± 18.22 µIU/ml) in those with non –controlled diabetes but this was not statistically significant (t = 1.081, df = 58, p = 0.284).

The mean HOMA-IR levels (7.80 ± 6.281) of the obese diabetic subjects with controlled diabetes was lower than the mean level ( 8.33 ± 8.20) in those with non-controlled diabetes. This difference was also not statistically significant (t = -.270, df = 58, p = 0.788).

71

Table 4.11: Comparison of biochemical parameters between non-obese T2DM subjects

with controlled and non-controlled diabetes.

Parameters Controlled DM Non-Controlled DM P-value n (%) = 23 (38.3%) n (%) = 37 (61.7%)

HbA1C (%) 5.9 ± 0.7 10.4 ± 2.4 0.0001*

Serum leptin (ng/ml) 8.18 ± 4.03 7.23 ± 2.92 0.300

Serum Insulin 8.07 ± 5.87 7.15 ± 1.67 0.371 (µIU/ml) HOMA-IR 2.77 ± 2.60 2.76 ± 1.00 0.982

Prevalence of IR 12 (52.2%) 28 (75.7%) 0.06 (n/%) DM = Diabetes Mellitus, IR = Insulin Resistance, *P < 0.05 is statistically significant

72

4.11 Relationship between serum leptin levels and glycaemic control in non-obese type 2

diabetic subjects

Table 4.11 shows the comparison of the mean levels of biochemical parameters between non- obese subjects with controlled and non-controlled diabetes. The mean serum leptin level (8.18 ±

4.03 ng/ml) in the non-obese diabetic subjects with controlled diabetes was higher than the mean level ( 7.23 ± 2.92 ng/ml) in those with non -controlled diabetes but this was not statistically significant (t = 1.047, df = 58, p = 0.300). There was also no significant correlation between the serum leptin levels and HbA1C in the non-obese diabetic subjects with controlled diabetes (r = -0.096, p = 0.662) and in the non-obese diabetic subjects with non-controlled diabetes (r = -0.202. p = 0.231) as shown in table 4.10.

The mean serum insulin levels (8.07 ± 5.87 µIU/ml) in the non-obese diabetic subjects with controlled diabetes was also higher than the mean level (7.15 ± 1.67 µIU/ml) in those with non - controlled diabetes but this was not statistically significant (t = ,902, df = 58, p = 0.371). The mean HOMA-IR level (2.77 ± 2.60) in the non-obese diabetic subjects with controlled diabetes was slightly higher than the mean level ( 2.76 ± 1.0) in those with non –controlled diabetes. This difference was also not statistically significant (t = 0.22, df = 58, p = 0.982).

73

CHAPTER FIVE

5.0: DISCUSSION

5.1: Preamble

The prevalence of obesity is rising globally and this rising trend has been recognized as a major driver of the increasing prevalence of type 2 diabetes.7 Obese subjects, especially females, are also known to have high circulating levels of leptin.18, 19 Leptin, in addition to its ability to inhibit energy intake and increase energy expenditure also has ability to regulate glucose metabolism.13

Most obese subjects have leptin resistance,2 hence this puts them at risk of type 2 diabetes, a condition characterized by chronic hyperglycaemia as a result of impaired glucose metabolism.

5.2: Socio-Demographic Characteristics of Study Population

This was a study of serum leptin, serum insulin and HOMA-IR in 180 female Nigerians in Ile-

Ife. The age range of subjects in this study was 34 to 64 years. There were three groups consisting of 60 subjects in each group. The mean ages of subjects in each group were comparable and similar to that observed in Turkish study.58 These females were mainly traders

(44.4%) and teachers (22.2%) which appear to be the most common occupation for females in our environment. The educational attainments and social habits of subjects were similar in obese and non-obese groups thus suggesting that these attributes may not explain any difference that existed among of the groups of study subjects.

5.3: Clinical Characteristics of Study Population

The mean duration of T2DM was shorter in obese T2DM subjects compared to non-obese T2DM subjects. It could be that non-obese T2DM subjects were also obese initially but had been

74 subjected to longer period of education on life style modification and treatment that could have resulted in their present body mass index though 71.7% of them still had central obesity.

The prevalence of previously diagnosed hypertension in obese T2DM and non-obese T2DM

Subjects were 76.7% and 63.3 % respectively, though about one third of the obese non-diabetic subjects were also hypertensive. This is not surprising as hypertension and T2DM are said to be in tandem. These finding are in keeping with the presence of metabolic syndrome in our subjects wth hypertension, obesity and T2DM being essential components of the metabolic syndrome,67 that is associated with increased risk of cardiovascular morbidity and mortality.

Family history of T2DM and obesity was much higher in the obese T2DM subjects compared with non-obese T2DM subjects . Similarly, family history of obesity was more in the obese subjects compared with non-obese subjects. This could affirm the familial tendencies found in certain non-communicable diseases such as T2DM and obesity.

Twin studies have demonstrated that familial aggregation of obesity has a genetic component and is not only due to cultural or environmental factors clustered in families.90 In addition, linkage studies have also identified markers and genes related to obesity in virtually all human chromosomes.90 This study revealed that 83.3% of the obese T2DM subjects, 75.0% of the obese non-diabetic subjects and 41.7% of the non-obese T2DM subjects had family history of obesity

75 thus supporting the strong familial tendency for obesity.

Majority of the subjects in each of the groups had central obesity as documented by waist circumference irrespective of their BMI. 100% of obese T2DM, 98.3% of obese non-diabetic,

and at least 70% of non-obese subjects had central obesity respectively. This high prevalence of central obesity among diabetic subjects was similar to that reported by Fasanmade et al 36 in

Lagos among Nigerian females with T2DM. Central obesity is particularly recognized as an independent risk factor for increased cardiovascular morbidity and mortality.

5.4: Comparison of serum leptin levels in the various groups.

Serum leptin levels was significantly higher in both obese subjects with or without type 2 diabetes mellitus than in non-obese type 2 diabetic subjects. The higher levels of leptin in obese than in non-obese subjects is most probably due to the fact that leptin is produced by adipose tissue in proportion to the amount of the adipose tissue in the body. That is the higher the body mass of adipose tissue, the higher the circulating levels of leptin.27, 91 Higher serum leptin levels in obese subjects was had been previously reported, 16, 18 although when compared to the levels reported in other populations,20, 47 the serum leptin levels in our subjects were lower. This is probably due to ethnic variations in serum levels of leptin as a result of variation in the severity of obesity.19, 20 Luke et al.,20 demonstrated that serum leptin levels in Nigerians were lower when compared to that of Jamaicans and Americans respectively.

76

Our study also showed that levels of serum leptin in obese non-diabetic subjects and obese type 2 diabetic subjects were similar. Liuzzi et al.,18 also found no statistically significance difference in serum leptin levels of their obese diabetic subjects when compared with obese non-diabetics, while Guler et al.,17 reported that leptin levels were not affected by the presence or absence of type 2 diabetes mellitus among Turkish women like our study.

Moreover, Buyukbese et al.,58 in a study among Turkish obese women with and without type 2 diabetes mellitus demonstrated a significantly higher serum level of leptin in the group without type 2 diabetes melltus. This difference in finding could probably be as a result of variation in insulin secretion in T2DM since insulin is also known to increase leptin production.57 The non - obese type 2 diabetic subjects group in our study had the lowest serum levels of leptin which is not unexpected considering their body mass index. Their leptin levels were also similar to the levels previously reported for non –obese females with type 2 diabetes mellitus in Nigeria ,56 perhaps because they all shared a common ethnic background.

Many investigators demonstrated that leptin had a significant correlation with BMI.20, 52, 58, 92 In our study also leptin had a significant correlation with BMI but only in the obese non-diabetic subjects. This trend was also observed in the relationship between serum leptin and serum insulin. The poor correlation between serum leptin levels, with BMI and serum insulin levels in diabetic subjects may be a reflection of anti-diabetic therapy that modulates insulin secretion and thus influencing leptin secretion.17 Leptin had a significant inverse correlation with HOMA-IR in obese T2DM subjects and no correlation with HOMA-IR in non-obese subjects while it had had a significant positive correlation with HOMA-IR in obese non diabetic subjects. This suggests that leptin may reduce insulin resistance in obese T2DM subjects and therefore be a potential therapeutic agent.

77

The levels of fasting lipid profiles (HDL- Cholesterol, LDL-Cholesterol, Total-Cholesterol, and

Triglycerde) observed in our study were similar in all subject groups and may be due to the fact that some of our diabetic subjects were already on lipid lowering drugs.

5.5: Relationship between serum leptin levels and glycaemic control in female subjects with

type 2 diabetes.

Serum leptin levels were higher in the obese type 2 diabetic subjects with controlled diabetes than the levels in those with non-controlled diabetes though this difference was not statistically significant. Buyukbese et al,47 had previously reported significantly elevated levels of leptin in obese female subjects with controlled diabetes. Among the non-obese type 2 diabetic subjects in this study, those with controlled diabetes also had a non-significant elevation in their serum leptin. The elevated serum leptin levels in subjects with controlled diabetes may be attributable to the known regulatory function of leptin on glucose metabolism.13, 17 Elevated serum leptin levels therefore appear to be good for glycaemic control.

A previous study demonstrated a weak but significant negative correlation between serum levels of leptin and glycaemic control before and after a period of treatment of DM.17 Our study also demonstrated a weak positive but non-significant correlation of serum leptin levels and glycaemic control (HbA1C) in both obese T2DM subjects and non-obese T2DM subjects. This variation in findings may all be due to the effect of DM treatments such as insulin secretagogues and insulin sensitizers commonly used by our patients.

78

5.6: Comparison of severity of insulin resistance in the various groups.

HOMA-IR is a surrogate marker of insulin resistance that has been found to be well correlated with the measure of insulin resistance determined by euglycaemic clamp which is the gold standard.85 The higher the HOMA-IR score, the higher the severity of insulin resistance.85, 86 In this study, HOMA-IR scores increased significantly across the groups with the lowest scores recorded in non-obese type 2 diabetic subjects and the highest scores recorded in obese type 2 diabetic subjects. The prevalence of insulin resistance was 100% among obese T2DM subjects,

98.3 % among obese non-diabetic subjects, and 66.7% among non-obese T2DM subjects. This finding further illustrates the fact that obesity is a risk factor for insulin resistance which is a known cause of type 2 diabetes mellitus. Oli et al.,89 in Enugu, Nigeria had previously shown that insulin resistance estimated by HOMA-IR is a major feature of type 2 diabetes mellitus in

Nigerians and that obesity consistently correlated with and predicted insulin resistance. The higher degree of insulin resistance among obese non -diabetic subjects in this present study also suggests that obese subjects can be targeted for the treatment of insulin resistance in order to prevent or delay future occurrence of type 2 diabetes mellitus in them.

There were no significant correlations between BMI and Waist Circumference (WC) with

HOMA-IR in both obese T2DM subjects and non-obese T2DM subjects but these correlations were demonstrated to be statistically significant in obese non-diabetic subjects. Liuzzi et al.,18 have demonstrated a significant positive correlation between HOMA-IR and BMI in a population of obese non-diabetic Italian subjects. The poor correlation between BMI and WC with HOMA-IR in all our diabetic subjects may be due to the modulatory effect of DM therapy on insulin resistance in obese subjects.

79

CHAPTER SIX

6.0 CONCLUSIONS AND RECOMMENDATIONS

6.1 Conclusions

This study has determined serum leptin levels in obese type 2 diabetic females, obese non- diabetic females and non-obese type 2 diabetic females. Serum leptin levels were significantly higher is all obese subjects than in non-obese subjects with no significant difference in the serum leptin levels of our obese women with and without type 2 diabetes mellitus.

Serum levels of leptin appear to be higher in both obese and non-obese diabetic subjects with controlled diabetes than in those with non-controlled diabetes. However, these higher levels of serum leptin in controlled diabetic subjects were not statistically significant.

HOMA-IR showed that obese type 2 diabetic subjects had the highest severity of insulin resistance followed by obese non-diabetic subjects and then non-obese diabetic subjects. The highest prevalence of insulin resistance of 100% were also found among the obese T2DM subjects.

6.2 Recommendations

1. Studies should be conducted to determine ethnic variation in the serum levels of leptin in

our environment.

2. In view of the potential therapeutic role of leptin on control of insulin resistance in obese

T2DM subjects suggested by our study, further study should be conducted to determine

and ascertain if leptin has any therapeutic effect in reducing insulin resistance in obese

T2DM subjects.

80

3. Future study should be conducted to determine if there is any variation in the relationship

between serum leptin levels and glycaemic control before and after both short and long

term treatement of T2DM and thus ascertain the effect of various DM therapeutic agents

on this relationship in obese T2DM subjects.

4. Since this study showed higher severity of insulin resistance state in all obese subjects,

they should be targeted for treatment and be advised regularly on life style modifications

to prevent or delay onset of T2DM or to improve insulin sensitivity.

6.3 Limitations of the study

Ø Inability to determine the body fat composition with the aid of Computerised

Tomography or Magnetic Resonance Imaging due to financial constraints. This

would have helped to distinguish true obesity from pseudo-obesity and also help

to properly ascertain the pattern of body fat distribution.

Ø Inability to perform oral glucose tolerance test on obese non-diabetic subjects in

order to exclude subjects who may have impaired glucose tolerance despite

fasting normoglycaemia.

Ø Inability to perform other biochemical tests that could have helped to further

screen and exclude subjects with other causes of obesity and diabetes such as

Cushing’s syndrome, hypothyroidism, growth hormone deficiency, polycystic

ovarian syndrome, e.t.c due to financial constraints.

81

REFERENCES

1. Zamboni M, Mazzali G, Zoico E, Harris TB, Meigs JB, Di Francesco V, et al. Health

consequences of obesity in the elderly: a review of four unresolved questions. Int J Obes

(Lond)2005;29(9):1011-29.

2. Enriori PJ, Evans AE, Sinnayah P, Cowley MA. Leptin resistance and obesity. Obesity

(Silver Spring)2006;14 Suppl 5:254S-8S.

3. Dyson PA. The therapeutics of lifestyle management on obesity. Diabetes Obes

Metab2010;12(11):941-6.

4. Diamant AL, Babey SH, Wolstein J, Jones M. Obesity and diabetes: two growing

epidemics in California. Policy Brief UCLA Cent Health Policy Res2010(PB2010-7):1-

12.

5. Goldstein BJ. Insulin resistance: from benign to type 2 diabetes mellitus. Rev Cardiovasc

Med2003;4 Suppl 6:S3-10.

6. Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates

for the year 2000 and projections for 2030. Diabetes Care2004;27(5):1047-53.

7. Yach D, Stuckler D, Brownell KD. Epidemiologic and economic consequences of the

global epidemics of obesity and diabetes. Nat Med2006;12(1):62-6.

8. World Health Organization. Global health risks : mortality and burden of disease

attributable to selected major risks. Geneva, Switzerland: World Health Organization;

2009.

9. Djiane J, Attig L. Role of leptin during perinatal metabolic programming and obesity. J

Physiol Pharmacol2008;59 Suppl 1:55-63.

82

10. Olatunbosun ST, Kaufman JS, Bella AF. Prevalence of obesity and overweight in urban

adult Nigerians. Obes Rev2011;12:233-41.

11. Akintomide AO, Adedoyin RA, Adebayo RA, Balogun MO, Nbada CE, Olanrewaju TM,

et al. Relationship between adiposity and blood pressure among semi-urban adult of Odo-

Ogbe community in Ile-Ife,Nigeria. Nigerian Journal of Health Sciences 2009;9 (2):11-8.

12. Padwal RS, Sharma AM. Prevention of cardiovascular disease: obesity, diabetes and the

metabolic syndrome. Can J Cardiol2010;26 Suppl C:18C-20C.

13. Dong F, Ren J. Fitness or fatness--the debate continues for the role of leptin in obesity-

associated heart dysfunction. Curr Diabetes Rev2007;3(3):159-64.

14. de Luis DA, Perez Castrillon JL, Duenas A. Leptin and obesity. Minerva

Med2009;100(3):229-36.

15. Girard J. Is leptin the link between obesity and insulin resistance? Diabetes

Metab1997;23 Suppl 3:16-24.

16. Esteghamati A, Khalilzadeh O, Anvari M, Rashidi A, Mokhtari M, Nakhjavani M.

Association of serum leptin levels with homeostasis model assessment-estimated insulin

resistance and metabolic syndrome: the key role of central obesity. Metab Syndr Relat

Disord2009;7(5):447-52.

17. Guler S, Cakir B, Demirbas B, Gursoy G, Serter R, Aral Y. Leptin concentrations are

related to glycaemic control, but do not change with short-term oral antidiabetic therapy

in female patients with type 2 diabetes mellitus. Diabetes Obes Metab2000;2(5):313-6.

18. Liuzzi A, Savia G, Tagliaferri M, Lucantoni R, Berselli ME, Petroni ML, et al. Serum

leptin concentration in moderate and severe obesity: relationship with clinical,

83

anthropometric and metabolic factors. Int J Obes Relat Metab Disord1999;23(10):1066-

73.

19. Perez F, Santos JL, Albala C, Calvillan M, Carrasco E. [Obesity and leptin association in

three Chilean aboriginal populations]. Rev Med Chil2000;128(1):45-52.

20. Luke AH, Rotimi CN, Cooper RS, Long AE, Forrester TE, Wilks R, et al. Leptin and

body composition of Nigerians,Jamaicans and US blacks. American Journal of Clinical

Nutrition. [Journal]. 1998;67:391-6.

21. Ajala MO, Ogunro PS, Idogun SE, Osundeko O. Relationship between Plasma Antioxidant

Status and Leptin in Controlled and Non‐Controlled Type 2 Diabetic Non‐Obese Women.

International Journal of Endocrinology and Metabolism2009;4:214-21.

22. Prentice AM. The emerging epidemic of obesity in developing countries. Int J

Epidemiol2006;35(1):93-9.

23. Vazquez G, Duval S, Jacobs DR, Jr., Silventoinen K. Comparison of body mass index,

waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis.

Epidemiol Rev2007;29:115-28.

24. Low S, Chin MC, Deurenberg-Yap M. Review on epidemic of obesity. Ann Acad Med

Singapore2009;38(1):57-9.

25. Abubakari AR, Lauder W, Agyemang C, Jones M, Kirk A, Bhopal R. Prevalence and

time trend in obesity among adulit West Africans population: a meta-analysis. Obesity

Reviews2008;9(4):297-311.

26. Richard D, Boisvert P. The Neurobiology of Obesity. Obesity. [Journal Article].

2006;14(Supplement):187S-I88S.

84

27. Wilborn C, Beckham J, Campbell B, Harvey T, Galbreath M, La Bounty P, et al. Obesity:

prevalence, theories, medical consequences, management, and research directions. J Int

Soc Sports Nutr2005;2:4-31.

28. Hirani V, Zaninotto P, Primatesta P. Generalised and abdominal obesity and risk of

diabetes, hypertension and hypertension-diabetes co-morbidity in England. Public Health

Nutr2008;11(5):521-7.

29. Yaskin J, Toner RW, Goldfarb N. Obesity management interventions: a review of the

evidence. Popul Health Manag2009;12(6):305-16.

30. World Health Organization. WHO Global Database on Body Mass Index. Geneva,

Switzerland:World Health Organization; 2010.

31. Johnson TO. Prevalence of overweight and obesity among Adult subjects of an urban

African population sample. British Journal Prev Soc Med1970;24:105-9.

32. Puepet FH, Zoakah AI, Chuwak EK. Prevalence of overweight and obesity among urban

Nigerian Adult in Jos. Highland Medical Research Journal2002;1(1):13-6.

33. Adedoyin RA, Mbada CE, Balogun MO, Adebayo RA, Martins T, Ismail S. Obesity

prevalence in adult residents of Ile-Ife, Nigeria. Nig Q J Hosp Med2009;19(2):100-5.

34. Adedoyin RA, Mbada CE, Ismail SA, Awotidebe TO, Oyeyemi AL, Ativie NR. Relative

prevalence of overweight and obesity among semi-urban dwellers in north-east Nigeria

using different measures of adiposity. Nigerian Journal of Health Sciences2010;10(1):14-

20.

35. Schienkiewitz A, Schulze MB, Hoffmann K, Kroke A, Boeing H. Body mass index

history and risk of type 2 diabetes: results from the European Prospective Investigation

85

into Cancer and Nutrition (EPIC)–Potsdam Study. American Journal of Clinical

Nutrition2006;84:427-33.

36. Fasanmade OA, Okubadejo NU. Magnitude and gender distribution of obesity and

abdominal adiposity in Nigerians with type 2 diabetes mellitus. Niger J Clin

Pract2007;10(1):52-7.

37. Fan W, Voss-Andreae A, Cao WH, Morrison SF. Regulation of thermogenesis by the

central melanocortin system. Peptides2005;26(10):1800-13.

38. Ricquier D. Respiration uncoupling and metabolism in the control of energy expenditure.

Proc Nutr Soc2005;64(1):47-52.

39. Seeley RJ, Woods SC. Monitoring of stored and available fuel by the CNS: implications

for obesity. Nat Rev Neurosci2003;4(11):901-9.

40. Saper CB, Chou TC, Elmquist JK. The need to feed: homeostatic and hedonic control of

eating. Neuron2002;36(2):199-211.

41. Wynne K, Stanley S, McGowan B, Bloom S. Appetite control. J

Endocrinol2005;184(2):291-318.

42. Zhang F, Chen Y, Heiman M, Dimarchi R. Leptin: structure, function and biology. Vitam

Horm2005;71:345-72.

43. Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM. Positional cloning

of the mouse obese gene and its human homologue. Nature1994;372(6505):425-32.

44. Thorburn AW, Ainslie DA, Fam B, Proietto J. Leptin in the pathophysiology of human

obesity and the clinical potential of leptin-based therapy. BioDrugs2000;13(6):391-6.

45. Schwartz MW, Woods SC, Porte D, Jr., Seeley RJ, Baskin DG. Central nervous system

control of food intake. Nature2000;404(6778):661-71.

86

46. Banks AS, Davis SM, Bates SH, Myers MG, Jr. Activation of downstream signals by the

long form of the leptin receptor. J Biol Chem2000;275(19):14563-72.

47. Friedman JM. Leptin and the regulation of body weight. Harvey Lect1999;95:107-36.

48. Ravussin E, Pratley RE, Maffei M, Wang H, Friedman JM, Bennett PH, et al. Relatively

low plasma leptin concentrations precede weight gain in Pima Indians. Nat

Med1997;3(2):238-40.

49. Montague CT, Farooqi IS, Whitehead JP, Soos MA, Rau H, Wareham NJ, et al.

Congenital leptin deficiency is associated with severe early-onset obesity in humans.

Nature1997;387(6636):903-8.

50. Strobel A, Issad T, Camoin L, Ozata M, Strosberg AD. A leptin missense mutation

associated with hypogonadism and morbid obesity. Nat Genet1998;18(3):213-5.

51. Clement K, Vaisse C, Lahlou N, Cabrol S, Pelloux V, Cassuto D, et al. A mutation in the

human leptin receptor gene causes obesity and pituitary dysfunction.

Nature1998;392(6674):398-401.

52. Considine RV, Sinha MK, Heiman;Mark.L, Kriauciunas A, Stephens TW, Nyce MR, et al. Serum

immunoreactive-leptin concentrations in normal-weight and obese humans. The New

England Journal of Medicine1996;334(5):292-5.

53. Montague CT, Prins JB, Sanders L, Digby JE, O'Rahilly S. Depot-and sex-specific

differences in human leptin mRNA expression:implications for the control of regional fat

distribution. Diabetes1997;46(3):342-7.

54. kolaczynski JW, Considine RV, Ohanannesian J, Marco C, Opentanova I, Nyce MR, et

al. Responses of leptin to short-term fasting and refeeding in humans:a link with

ketogenesis but not ketones themselves. Diabetes1996;45(11):1511-5.

87

55. Havel PJ, Townsend R, Chaump L, Teff K. High-fat meals reduce 24-h circulating leptin

concentrations in women. Diabetes1999;48(2):334-41.

56. Sinha MK, Ohanannesian JP, Heiman;Mark.L, Kriauciunas A, Stephens TW, Magosin S,

et al. Nocturnal rise of leptin in lean, obese, and non-insulin dependent diabetes mellitus

subjects. Journal of Clinical Investigation1996;97(5):1344-7.

57. Wabitsch.M, Jensen PJ, Blum W, F, Chrisoffersen CT, Englaro P, Heinze E, et al. Insulin

and cortisol promote leptin production in cultured human fat cell.

Diabetes1996;45(10):1435-8.

58. Buyukbese MA, Cetinkaya A, Kocabas R, Guven A, Tarakcioglu M. Leptin levels in

obese women with and without type 2 diabetes mellitus. Mediators Inflamm. [Research

Support, Non-U.S. Gov't]. 2004;13(5-6):321-5.

59. Steppan CM, Bailey ST, Bhat S, Brown EJ, Banerjee RR, Wright CM, et al. The

hormone resistin links obesity to diabetes. Nature2001;409(6818):307-12.

60. Shera AS, Jawad F, Maqsood A, Jamal S, Azfar M, Ahmed U. Prevalence of chronic

complications and associated factors in type 2 diabetes. J Pak Med Assoc2004;54(2):54-

9.

61. Straub RH, Thum M, Hollerbach C, Palitzsch KD, Scholmerich J. Impact of obesity on

neuropathic late complications in NIDDM. Diabetes Care1994;17(11):1290-4.

62. Maggio CA, Pi-Sunyer FX. Obesity and type 2 diabetes. Endocrinol Metab Clin North

Am2003;32(4):805-22, viii.

63. Flier SJ, Maratos-Flier E. Obesity. In: Kasper DL, Braunwald E, Fauci AS, Hauser SL,

Longo DL, Jameson JL, editors. Harrison's principle of Internal medicine. 16th ed. New

York: McGraw-Hill; 2005. p. 422-29.

88

64. Pi-Sunyer FX. The obesity epidemic: pathophysiology and consequences of obesity.

Obes Res2002;10 Suppl 2:97S-104S.

65. Richard D, Boisvert P. The role of gene regulation in obesity and its complications:

introduction. Int J Obes (Lond)2005;29 Suppl 1:S1-2.

66. Klein S, Wadden T, Sugerman HJ. AGA technical review on obesity.

Gastroenterology2002;123(3):882-932.

67. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome--a new world-wide definition. A

Consensus Statement from the International Diabetes Federation. Diabet

Med2006;23(5):469-80.

68. World Health Organization. Obesity : preventing and managing the global epidemic :

report of a WHO consultation. Geneva: World Health Organization; 2000.

69. National Heart Lung and Blood Institute., National Institute of Diabetes and Digestive

and Kidney Diseases (U.S.). Clinical guidelines on the identification, evaluation, and

treatment of overweight and obesity in adults : the evidence report. [Bethesda, Md.?]:

National Institutes of Health, National Heart, Lung, and Blood Institute; 1998.

70. Pouliot MC, Despres JP, Lemieux S, Moorjani S, Bouchard C, Tremblay A, et al. Waist

circumference and abdominal sagittal diameter: best simple anthropometric indexes of

abdominal visceral adipose tissue accumulation and related cardiovascular risk in men

and women. Am J Cardiol1994;73(7):460-8.

71. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and

its complications. Part 1: diagnosis and classification of diabetes mellitus provisional

report of a WHO consultation. Diabet Med1998;15(7):539-53.

89

72. World Health Organization. Waist circumference and waist–hip ratio: report of a WHO expert

consultation, Geneva, 8–11 December 2008. Geneva: World Health Organization; 2011.

73. Tzotzas T, Krassas GE, Doumas A. [Body composition analysis in obesity: radionuclide

and non radionuclide methods]. Hell J Nucl Med2008;11(1):63-71.

74. Woodrow G. Body composition analysis techniques in the aged adult: indications and

limitations. Curr Opin Clin Nutr Metab Care2009;12(1):8-14.

75. Jackson AS, Pollock ML. Generalized equations for predicting body density of men.

Biritish Journal of Nutrition1978;40:497-504.

76. Jackson AS, Pollock ML, Ward A. Generalized equations for predicting body density of

women. Medicine and Science in Sports Exercise1980;12:175-82.

77. Jaffrin MY. Body composition determination by bioimpedance: an update. Curr Opin

Clin Nutr Metab Care2009;12(5):482-6.

78. Sharma A, Kushner R. A proposed clinical staging system for obesity. International

journal of obesity2009;33(3):289-95.

79. Steinbeck K. Obesity: the science behind the management. Intern Med J2002;32(5-

6):237-41.

80. Caveney E, Caveney BJ, Somaratne R, Turner JR, Gourgiotis L. Pharmaceutical

interventions for obesity: a public health perspective. Diabetes,Obesity and

Metabolism2011;13(6):490-7.

81. Hilary K, Ronald EA, William HH. Global burden of diabetes,1995-2025: prevalence,

numerical estimates, and projections. Diabetes Care. [Journal]. 1998;21(9):1414-31.

90

82. International Diabetes Federation. IDF diabetes atlas: diabetes and Impaired glucose

tolerance 4th ed. Sicree R, Shaw J, Zimmet P, Baker IDI Heart and Diabetes Institute,

editors. Belgium: International Diabetes Federation; 2011.

83. Eng J. Sample Size Estimation: How Many Individuals Should Be Studied? 1.

Radiology2003;227(2):309.

84. Rosner B. Fundamentals of biostatistics. 5th ed. Pacific Grove, Calif: Duxbury; 2000.

85. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC.

Homeostasis model assessment: insulin resistance and beta-cell function from fasting

plasma glucose and insulin concentrations in man. Diabetologia1985;28(7):412-9.

86. Esteghamati A, Ashraf H, Khalilzadeh O, Zandieh A, Nakhjavani M, Rashidi A, et al.

Optimal cut-off of homeostasis model assessment of insulin resistance (HOMA-IR) for

the diagnosis of metabolic syndrome: third national surveillance of risk factors of non-

communicable diseases in Iran (SuRFNCD-2007). Nutr Metab (Lond)2010;7:26.

87. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo Jr. JL, et al.

Seventh report of the Joint National Committee on the Prevention, Detection, Evaluation,

and Treatment of High Blood Pressure (JNC 7): resetting the hypertension sails.

Hypertension2003;42(6):1206-52.

88. Barham D, Trinder P. An improved colour reagent for the determination of blood glucose

by the oxidase system. Analyst1972;97(1151):142-5.

89. Oli JM, Adeyemo AA, Okafor GO, Ofoegbu EN, Onyenekwe B, Chukwuka CJ, et al.

Basal insulin resistance and secretion in Nigerians with type 2 diabetes mellitus.

Metabolic syndrome and related disorders. [Research Support, N.I.H., Extramural].

2009;7(6):595-9.

91

90. Santos JL, Martinez JA, Perez F, Albala C. [Genetic epidemiology of obesity: family

studies]. Rev Med Chil2005;133(3):349-61.

91. Oshodi T, Ebuehi OA, Ojewunmi O, Udenze I, Soriyan T. Circulating adipokine levels in

type 2 diabetes mellitus in Lagos, Nigeria. Nig Q J Hosp Med2012;22(1):25-8.

92. Suzuki K, Ito Y, Ochiai J, Kusuhara Y, Hashimoto S, Tokudome S, et al. Relationship

between obesity and serum markers of oxidative stress and inflammation in Japanese.

Asian Pacific Journal of Cancer Prevention2003;4(3):259-66.

92

APPENDIX 1

PROFORMA

SECTION A: SOCIODEMOGRAPHIC DATA

Hospital / Identification number------

1) Age------

2) Marital status: (a) Married (b) Single (c) Separated (d) Divorced (e) Widowed

3) Religion a) Christianity (b) Islam (c) Others (Please specify) ------

4) Ethnicity: (a) Yoruba (b) Igbo (c) Hausa (d) Others specify------

5) Level of Education (a) None (b) Primary (c) Secondary (d) University (e) Others (Please specify)------

6a) Main Occupation------

6b) Husband’s main occupation ------

7) Parity: (a) Nullipara (b) Primipara (c) Multipara

8) Have you attained menopause ? (a) Yes, state duration in years------

SECTION B: MEDICAL HISTORY

9a) Type 2 DM present? (a)Yes (b) No

9b) If yes, Age at diagnosis (years)------

Duration of DM (years)------

Treatment type received in the last one month.------

10a) Hypertension Present? (a) Yes (b) No

93

10b) If yes, Age at diagnosis (years) ------

Duration of hypertension (years) ------

Treatment type for hypertension------

11a) Current use of lipid lowering drug? (a) Yes (b) No

11b) If yes, duration of treatment------

Type of lipid lowering agent being used------12) Family history of DM in first degree relation?(a)Yes (b) No (c) Don’t know

13) Family history of hypertension in first degree relation?(a)Yes (b) No (c) Don’t know

14) Family history of obesity in first degree relation?(a)Yes (b) No (c) Don’t know

15) Have you been fat from childhood? (a)Yes (b) No (c) Don’t know

16) Alcohol use-type, quantity and duration?------

17) Smoking history-type, quantity and duration------

SECTION C: CLINICAL EXAMINATION

18) Blood Pressure (mmHg)______

19) Weight in kg.______

20) Height in metre.______

21) Waist Circumference (cm).______

94

22) Hip Circumference (cm).______

23) BMI (kg/m2).______-

24) WHR.______

SECTION D: LABORATORY RESULT

25) FPG (mmol/L)______

26) HbA1c (%).______

27) Fasting Plasma insulin level (microIU/ml).______

28) Fasting Plasma leptin level (ng/ml).______

29) Fasting Lipid profile:

HDL (mmol/L)______

TG (mmol/L)______

LDL (mmol/L)______

Total Cholesterol (mmol/L)______

30) HOMA-IR______

95

APPENDIX 2

INFORMED CONSENT FORM

SECTION A : INFORMATION FOR PARTICIPANT

Dear Respondent,

This study aims to compare the amount of the body chemical messenger known as the leptin hormone in the blood of all the female participants who may or may not have higher body fat

(obesity) together with type 2 diabetes with the amount of the same hormone that is present in the blood of all the female participants who have a higher body fat only without a coexisting type

2 diabetes. This will require that the investigator take some blood samples in the morning after a period of overnight fast and also perform physical examination with anthropometric measurements for all participants. There is no potential harm that this study will inflict on you if you consent to be a participant. Your can also decide to withdraw your participation at any time.

This study will be done at no extra cost to you and your confidentiality shall be maintained.

By signing this form, you are indicating that you understand the nature of the research study and your role in the research and that you agree to participate in it.

SECTION B: CONSENT AND SIGNATURE

I ------,am stating that I understand the above information and consent to participate in this study.

…………………………………… …………………………………

Signature/thumbprint of participant/Date Signature of investigator/Date

......

Signature of witness/Date

96

APPENDIX 3

ETHICAL CONSIDERATIONS

Approval was obtained from the Research and Ethical Committee of Obafemi Awolowo

University Teaching Hospital, Ile-Ife. The patients that gave their consent after being briefed about the study were included in this study.

1. Right to decline.

Participants are free to decline participation and can withdraw from the study at

any point without reprisal or loss of benefit.

2. Translation of protocol to local language

The processes in the study will be interpreted in the local language and explained

to each participant for ease of understanding before asking for their signature.

3. Confidentiality of Data

Confidentiality shall be ensured by assigning a code number as an identifier to

each participant.

4. Beneficence to participants

Investigations required for the purpose of the study would be at no cost to the

participants.

5. Non malfeasance

All procedures carried out on the participants would be done with all carefulness for the patient, to ensure that no harm is done and their right is not infringed.

97

APPENDIX 4

98

APPENDIX 5

GLUCOSE OXIDASE METHOD

The glucose oxidase method of blood glucose estimation according to Trinder reaction is based on the oxidation of glucose present in the plasma by the enzyme glucose oxidase to form glucoronic acid with the liberation of hydrogen peroxide, which is converted to water and oxygen by the enzyme peroxidase. An oxygen acceptor takes up the oxygen and together with the phenol forms a pink colour chromogen (quinoneimine) which can be measured by the spectrophotometer at wavelength of 520nm.

Procedure: 1ml of glucose oxidase solution was added to a test tube containing 10 µl of plasma sample from centrifuged blood specimen in the fluoride oxalate bottles and 10 µl of standard glucose solution. Tests on the standard glucose were performed in the duplicate and there was a blank test tube containing glucose oxidase solution and 10µl of distilled water.

Three test tubes containing plasma samples of known glucose concentrations were also included in each assay run. The tubes were incubated for 15 minutes at room temperature. Thereafter, the optical densities (absorbance) were read off with the spectrophotometer at a wavelength of

520nm. The blank test tube was used as a reference point against which the optical densities of all other tubes were determined. The optical density for the plasma glucose was compared with that for the standard glucose solution which has a known glucose concentration. The mean values from repeated test on the standard glucose preparation were used in the test sample.

99

The level of plasma glucose was then estimated based on the following formula:

 

    ×    = ABSORBANCE OF STANDARD

PRECISION OF PLASMA GLUCOSE ASSAY

Intra Assay Precision Inter Assay Precision Mean Glucose Concentration 4.84 mmol/l 4.84 mmol/l (mmol/l) Coefficient of Variation 1.2% 2.7% (CV%) Number of Samples (n) 20 25

100

APPENDIX 6

MEASUREMENT OF GLYCOSYLATED HAEMOGLOBIN

Glycosylated haemoglobin (HbA1C) was estimated using whole venous blood samples with the aid of Bio-Rad in2it (I) system which allows the in vitro quantitative determination of HbA1C.

Principle: This in2it Test uses the well-established method of boronate affinity chromatography to separate the glycosylated haemoglobin fraction from the non-glycosylated fraction. The in2it

(I) Analyser is a single-wavelength (440nm) photometer designed as a fully automated system.

The test cartridge contains the sample reagent, as well as wash solution and elution buffer.

Procedure: After setting up the analyser and running both the system check cartridge and quality controls, the venous blood was collected using a specially designed blood key, which was clicked in place through a blue blood port into the test cartridge. The handle of the key was removed so that the key will be smooth with the surface of the test cartridge and then the test cartridge was immediately placed in the analyser. From this point the reaction is automatic.

The sample reagent lyses the red blood cells and after mixing and incubation, the glycosylated haemoglobin binds to the boronate affinity resin. The liquid then flows through the central hub of the test cartridge. A frit in the hub retains the affinity resin bound with glycosylated haemoglobin; the non-glycosylated fraction is collected and measured photometrically. Wash solution is then released, flowing through the central hub to wash the affinity resin. Elution is released, flowing through the central hub to elute the glycosylated haemoglobin off the boronate affinity resin; this glycosylated haemoglobin fraction is then photometrically measured.

101

The percentage glycosylated haemoglobin (% HbA1C ) is calculated from the absorbances using the following formula:

% HbA1C = M (Aglycated × 100) ÷ [ (Aglycosylated + Anom-glycosylated ) + C]

M and C are the slope and intercept factors respectively and are used to correct the value for the

Diabetes Control and Complication Trial (DCCT) calibration. When the test finished, the %

HbA1C result was displayed by the analyser. The overall precision for all tests performed had a coefficient of variation (CV) less than 5%.

102

APPENDIX 7

LIPID PROFILE ESTIMATION

TOTAL CHOLESTEROL: Total cholesterol was estimated by the enzymatic method. The test principle is based on the fact that cholesterol esters present in plasma are hydrolysed by cholesterol esterase and the cholesterol formed are then measured by oxidizing with cholesterol oxidase to form hydrogen peroxide. The peroxide is then reacted with 4-aminoantipyrine and phenol in the presence of peroxidase to form the red quinoneimine dye. The intensity of the dye formed is directly proportional to the level of cholesterol present in the sample.

Procedure: 10 µl of plasma sample were thoroughly mixed with 1000 µl of reagent and the mixture was incubated at room temperature for 10 minutes. Thereafter, the absorbance of the sample and standard were measured photometrically by the auto-analyser at 600 nm against the reagent blank.

Intra-assay Precision = 3.73 % at 1.71 mmol/l and 3.84 % at 7.70 mmol/l

Inter-assay Precision = 1.33 % at1.67 mmol/l and 1.39 % at 7.52 mmol/l

TRIGLYCEDRIDE: Triglyceride in the plasma sample was measured by means of the coupled reactions using enzymatic method. The test principle is based on the fact that triglycerides present in plasma are hydrolysed by lipase and glycerol kinase to form glycerol-3-phosphate which is then oxidised by glycerol-3-phosphate oxidase to produce hydrogen peroxide. The peroxide is then reacted with 4-aminoantipyrine and 4-chlorophenol in the presence of peroxidase to form the red quinoneimine dye. The intensity of the dye formed is directly proportional to the level of triglyceride present in the sample.

103

Procedure: 10 µl of plasma sample were thoroughly mixed with 1000 µl of reagent and the mixture was incubated at room temperature for 10 minutes. Thereafter, the absorbance of the sample and standard were measured photometrically by the auto-analyser at 600 nm against the reagent blank.

Intra-assay Precision = 3.29 % at 0.308mmol/l and 1.77 % at 5.61 mmol/l

Inter-assay Precision = 3.51 % at 0.642 mmol/l and 1.33 % at 3.03 mmol/l

LDL CHOLESTEROL: LDL cholesterol was measured with the aid of Randox direct LDL cholesterol kits which are liquid ready to use two-point endpoint assays based on clearance method. In this clearance method, selective detergents release LDL cholesterol from chylomicrons (CM), VLDL and HDL and is then removed by the action of cholesterol esterase and oxidase. LDL cholesterol is then released in the second step of the reaction by surfactant and removed by enzymes. The assay consists of two distinct steps. (1) Clearance step and (2) Assay step.

REACTION PRINCIPLE

CLEARANCE STEP

CM, HDL, VLDL Cholesterol Esterase Cholestenone + Hydrogen Peroxide Cholesterol Oxidase Catalase

Water + Oxygen

ASSAY STEP

LDL Cholesterol Esterase Cholestenone + Hydrogen Peroxide Cholesterol Oxidase Peroxidase

(Quinone Pigment) Colour Development

Catalase is inhibited in the second step by Sodium Azide

104

Procedure: This procedure was carried out automatically on plasma samples in URIT 8020 chemistry auto-analyser.

Intra-assay precision = 1.47 % at 2.74 mmol and 2.99 % at 4.42 mmol/l;

Inter-assay precision = 2.5 % at 2.52 mmol/l and 1.58 % at 5.34 mmol/l

HDL CHOLESTEROL: Randox clearance method was used. Non-HDL lipoproteins are removed in the first step of the reaction (clearance step), enhancing the specificity of the assay at the detection strep even in patient samples with abnormal lipoproteins.

REACTION PRINCIPLE

CLEARANCE STEP

CM, LDL, VLDL Cholesterol Esterase Cholestenone + Hydrogen Peroxide Cholesterol Oxidase Catalase

Water + Oxygen

ASSAY STEP

HDL Cholesterol Esterase Cholestenone + Hydrogen Peroxide Cholesterol Oxidase Peroxidase

(Quinone Pigment) Colour Development

Catalase is inhibited in the second step by Sodium Azide Procedure: This procedure was carried out automatically on plasma samples in URIT 8020 chemistry auto-analyser.

Intra-assay Precision = 1.80 % at 0.788mmol/l and 3.11 % at 2.00 mmol/l

Inter-assay Precision =2.81% at 0.817 mmol/l and 2.73 % at 2.01mmol/l

105

Generally for all these tests, the intensity of the dye (pigment) formed is directly proportional to the level of cholesterol present in the sample. The absorbance of the quinoneimine dye produced by the sample and standard was then measured photometrically against that of reagent blank using automated analyser.

The results of the total cholesterol, triglyceride, HDL cholesterol and LDL cholesterol concentrations in the sample were displayed by the auto-analyser respectively following calculation using the following formula:

Cholesterol Concentration of the Sample

= Absorbance of Sample × Concentration of Standard ÷ Absorbance of Standard.

106

APPENDIX 8

SERUM LEPTIN IMMUNOASSAY TEST

FASTING SERUM LEPTIN: This was measured by double assay from the sera of subjects as total serum leptin. This quantitative estimation of human serum leptin assay was done using the

Human leptin kit with batch number 1242-6 (supplied by Diagnostic Automation, Inc, Calabasas,

CA 91302USA.) using a Chemwell 2910 microwell ELISA immuno-analyser. The method of assay was sandwich microwell enzyme linked immunosorbent assay (ELISA) based on the principle of solid phase enzyme linked immunosorbent assay.

A Sandwich ELISA on solid phase immunosorbent assay microtiter wells coated with monoclonal anti-leptin antibodies was used. All standards, samples, and controls were run in duplicate concurrently under the same condition. As pre-programmed on the auto-analyser,15ul of each standard solution (calibrants), control solution and patients sera were pipetted into appropriate wells. Then 100 µl of assay buffer was added into each well and mixed thoroughly for 10 seconds. Thereafter the assay tray was incubated appropriately for 120 minutes at room temperature within the inherent environment of the auto-analyzer without covering the plate. At the end of the incubation period, the wells were washed thrice with 300 µl of diluted wash solution following which all microwells were aspirated dry.

Next 100 µl of antiserum was dispensed into each well and incubated for 30 minute at room temperature followed by the aspiration of well to dryness again and repeated washing of the well with 300 µl of diluted wash solution thrice. For sandwich complex, 100 µl of enzyme complex was dispensed in each of the wells and enzyme conjugate complex mixture was then incubated again for 30 minute at room temperature and washed thrice as previously done. Thereafter, all

107 well were aspirated to dryness. Fianally,100 µl of substrate solution was added to each well followed by incubation for 15 minutes at room temperature and thereafter, the reaction was then terminated by dispensing 50 µl of stop solution (0.5M H2SO4). The autoanylyser gave the reading of the leptin concentration generated by reading colour intensity of the microwell contents at a programmed wavelength of 450 nm. Individual serum leptin concentrations were determined by automated interpreting against standard curve generated by the auto-analyser.

Since sample size was larger than could be accommodated at once on the assay tray of the analyser, reliability of assays were ensured by insertion of the two levels of control sera

(provided in the kit) at the first arm and latter end of each assay trays. Inter-batch and intra-batch assay precisions were also ensured by strategically repeating previously assayed samples.

Assay sensitivity: 0.3ng/ml

Specificity of Antibodies (Cross Reactivity) for human insulin: 100%

Intra assay coefficient of variation (CV): 6.42%)

Inter assay coefficient of variation (CV): 10.11%

The expected values for a normal weight male = 3.84 ± 1.79ng/ml and for a normal weight female = 7.36 ± 3.73ng/ml.

108

APPENDIX 9

SERUM INSULIN IMMUNOASSAY TEST

FASTING SERUM INSULIN: Double assay for serum insulin was carried out by a quantitative method with microwell enzyme linked immunosorbent assay ( ELISA) human insulin test kits (supplied by Cusabio Biotech Co Ltd.,USA) were performed by Chemwell 2910

Auto-analyser . The test principle is based on sandwich immunoenzymometric assay. In this procedure, the immobilization takes place during the assay at the surface a microplate well through the interaction of streptavidin coated on the well and exogenously added biotinylated monoclonal insulin antibody.

As pre-programmed on the auto-analyser, 50µl each of the standard calibrator, control and patient sera were respectively pipetted into the designated microwells. This was followed by addition of 100µl of insulin enzyme (ELISA) reagent into each well. All the samples were then incubated at 370C for 120mins, after which the various wells were automatically washed three times with 10 seconds of swirling in between each cycle of washing.

The Microwells were aspirated dry by the suction probes of the washing chamber of the machine. After the aspiration by the washing chamber, 100µl of premixed substrate solutions A and B were discharged into each microwell. The reaction microplates were then incubated for another 15mins after which all reactions were terminated with 50µl of the stopping solution.

The final stage of the assay was automated spectrophotometric measurement of the absorbances of the sera, standards and controls which were measured at 450nm and 620nm respectively. All results including controls and sera were read against standard calibrators. Individual serum

109 insulin concentrations were determined by automated interpreting against standard curve generated by the auto-analyser.

Since sample size was larger than could be accommodated at once on the assay tray of the analyser, reliability of assays were ensured by insertion of the two levels of control sera

(provided in the kit) at the first arm and latter end of each assay trays. Inter-batch and intra-batch assay precisions were also ensured by strategically repeating previously assayed samples.

The expected reference values for normal adults range from 0.7 to 9.0 µIU/ml and values for adults with type 2 diabetes mellitus range from 0.7 to 25 µIU/ml. The sensitivity of this assay was 0.75µIU/ml and the test has no cross reactivity with C-peptide, proinsulin and glucagon. The intra assay coefficient of variation (CV) was 6.0%, while the inter assay coefficient of variation

(CV) was 7.4%

110

APPENDIX 10

BUDGETED COST OF PROJECT

Test kits for Leptin N 300,000

Test kits for Insulin 240,000

Littman Stethoscope 15,000

Accuson Sphygmomanometer 15,000

Seca Stadiometer 18,000

Seca Weighing Scale 30,000

Fasting Plasma Glucose 36,000

Fasting Lipid Profiles 180,000

Glycosylated Haemoglobin 240,000

Methylated spirit 1,000

Latex gloves 3,600

Needles and syringes 3,600

Cotton wool 1, 200

Sample bottles Plain 30,000 Lithium heparin 7,500 KEDTA 7,500 Fluoride Oxalate 7,500 Miscellaneous 50,000

TOTAL ...... N1,185, 900.00

111

112