Nutrient Intake in the Kingdom of Tonga

Associations with Overweight, Obesity and Glucose Tolerance

Soana Muimuiheata

Thesis submitted in fulfillment of the degree of Master of Science

University of New South Wales

March 2007

ABSTRACT

Diabetes mellitus, cardiovascular disease and other non-communicable diseases (NCD) have become the major cause of premature death, morbidity and disability in many Pacific countries including Tonga. Several population-based surveys have suggested that changes from a traditional to a modern way of life have enhanced the development of NCD. These diseases are multifactorial metabolic disorders where risk factors include hyperglycaemia, obesity, hypertension, lipid abnormalities, physical inactivity and poor nutrient intake. There has been little research which has specifically examined detailed food intake and nutrient composition in the Tongan population.

Aims - to determine the national pattern of food and nutrient intake in Tonga and to identify associations between food and nutrient intake and overweight, obesity and glucose tolerance.

Research Design and Methods – The survey was conducted in two parts, Tongatapu in 1998 and Vava‟u and Ha‟apai in 2000. A multi-stage cluster sampling design was used to select a representative sample of 1024 people age 15 years and older from the Tongan population. Information about the usual food and nutrient intake was collected by Food Frequency Questionnaire, and analysed by the Australian Food Works program. Lifestyle behaviours such as physical activity, alcohol and smoking status, the use of traditional medicine, occupation and religious practices were also collected. Anthropometric and clinical measurements – weight, height, body mass index, body fat, blood pressure, lipid profiles, fasting glucose, HbA1c, creatinine and microalbumin levels were measured.

Results – The Tongan population is consuming a high carbohydrate (59% total energy intake), moderate protein (15% total energy intake) and low fat (22% total energy intake) diet, which is consistent with the WHO recommendations for a healthy diet. However the total daily energy intake is high. The mean (± SD) daily total energy intake was 4856 ± 2304 kcal and males consumed significantly more than females (5308 ±2366 vs 4522 ± 2201 kcal, p=0.009). This resulted in the diet exceeding the recommended dietary requirements for all nutrient components. There were minor differences in nutrient intake patterns in the more urban Tongatapu compared with the more rural Vava‟u/Ha‟apai. Alcohol consumption and smoking was much more ii

common among men than the women and was higher in Tongatapu than Vava‟u/Ha‟apai participants. Males reported more physical activity than females.

The prevalence of overweight and obesity in Tonga is very high – 93% in women and 84% in men. There has been a significant increase in prevalence of obesity among Tongans which has increased at least four-fold in men and almost doubled among women in the past 12 years. Prevalence rates were similar in rural and urban areas.

Conclusion: Tonga is experiencing an increasing problem of overweight and obesity which is a major risk factor for a number of non-communicable diseases including diabetes and cardiovascular disease. A high dietary energy intake could be a contributing factor to the increasing overweight and obesity problem.

The findings of this study have important implications for public health efforts and policy development to contain the epidemic of non-communicable diseases in Tonga.

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ACKNOWLEGEMENT

I would like to express my sincere gratitude to my supervisor, Professor Stephen Colagiuri for his direction and guidance throughout the course of this work. His expertise, commitment and constructive criticism add value to this research. It has been a privilege to be associated with such a dedicated and enthusiastic person towards health and research.

I would like to thank my co-supervisor Dr. Taniela Palu for his guidance, support and encouragement throughout this research work. His enormous trust and relentless efforts have helped to see me complete this research activity. I would also like to thank my colleagues at the National Centre for Prevention and Control of Diabetes and Cardiovascular Diseases, Vaiola Hospital, for their great support throughout this work.

I would like to thank Associate Professor Ruth Colagiuri for the on-going support, encouragement and willingness to maximize my working opportunity. Her commitment and dedication for excellence have encouraged me to work through this research. I would also like to thank the survey team and staff of Diabetes Centre, Prince of Wales Hospital for their support and assistance throughout this research. I am extremely grateful to the survey statistician, Zafrul Huzzain for his expertise and help in statistical theory, analysis and application.

I also would like to thank the Ministry of Health and the people of Tonga for allowing me to undertake this research work, and the Australian government for providing financial support. I also would like to thank my employer in New Zealand, TaPasefika Health Trust and South Seas Health Care for supporting me in my study.

Finally, I would like to acknowledge my sincere gratitude and appreciation to my parents, the late Sione and Salote Muimuiheata, and my sisters, Popua, Mele, Simaima, Temaleti, Hulita, my brothers, Futa, Kava, Niu, and my in-laws, nieces and nephews for their love, prayers and support. Special thanks to all my friends and relatives for all their contribution and support. Above all, I am forever grateful to God for his wisdom and guidance as he led me through this life and may his name be glorified and honoured.

Table of Contents

Page

Tile Page i Abstract ii Acknowledgment iv Table of Contents v List of Figures xii List of Tables xiii Certificate of Originality xvi Glossary of Acronyms xvii

CHAPTER 1 INTRODUCTION 1.1 About Tonga: The Land and it‟s people 1 1.1.1. Geography 1 1.1.2. Population 3 1.1.3. History and Culture 4 1.1.4. Infrastructure 5 1.1.5. Health Status in Tonga 6 1.1.5.1. Mortality and Morbidity Rates in Tonga 6 1.2. Diabetes and Non-Communicable Diseases 7 1.2.1. Diabetes 7 1.2.1.1. Definition 7 1.2.1.2. Classification 8 1.2.1.2.1. Type 1 Diabetes 8 1.2.1.2.2. Type 2 Diabetes 9 1.2.1.2.3. Gestational Diabetes Mellitus 9 1.2.1.2.4. Other Specific Types 9 1.2.1.2.5. Impaired Glucose Regulation –Impaired 10 Glucose Tolerance and Impaired Fasting Glycaemia

1.2.2 Diabetes and Cardiovascular Disease in Tonga and in the 11 Pacific Countries v

1.2.2.1. Brief Review 11 1.2.2.2. Diabetes Prevalence in the Pacific Countries 12 1.2.2.3. Diabetes Prevalence in Tonga 14 1.2.2.4. Prevalence of Diabetes Complications in Tonga 15

1.2.3. Risk Factors for Diabetes and Cardiovascular Disease 15 1.2.3.1. Brief Overview 15 1.2.3.2. The Metabolic Syndrome 16 1.2.3.3. Overweight and Obesity 18 1.2.3.3.1. Brief Overview 18 1.2.3.3.2. Body Mass Index 19 1.2.3.3.3. Waist Circumference and Waist to Hip Ratio 20 1.2.3.3.4. Prevalence of Overweight and Obesity in 22 Pacific Countries 1.2.3.3.5. Prevalence of Overweight and Obesity 22 in Tonga 1.2.3.4. Thrifty Genotype 27 1.2.3.5. Hypertension 28 1.2.3.5.1. Brief Overview 28 1.2.3.5.2. Hypertension in Tonga 28

1.3. Food and Nutrient Intake 30

1.3.1. Brief Overview 30 1.3.1.1. Food and Culture 31 1.3.1.2. Food Groups 32 1.3.1.3. Food and Nutrition Guidelines 33 1.3.1.4. Recommended Dietary Intake 34

1.3.2. Nutrient Intake and Non-Communicable Diseases 35 1.3.2.1. Nutrients, Diabetes and Cardiovascular Disease Risk Factors 37 1.3.2.1.1. Current nutrition recommendations for diabetes and cardiovascular risk factors 38 1.3.2.1.2. Total Energy Intake 38 1.3.2.1.3. Dietary Fats 39 1.3.2.1.4. Carbohydrates 40 1.3.2.1.5. Dietary Fibre 41 1.3.2.1.6. Glycaemic index 42 1.3.2.1.7. Proteins 43 1.3.2.1.8. Vitamins and Minerals 43 1.3.2.2.Food and Nutrient Intake in the Pacific Countries 44 1.3.2.3.Food and Nutrient Intake in Tonga 46

1.4. Lifestyle Risk Factors 49

1.4.1. Exercise and Physical Activity 49 1.4.1.1. Brief Overview 49 1.4.1.2. Physical Activity, Diabetes and Cardiovascular Disease 50 1.4.1.3. Physical Activity in Tonga 50 1.4.2. Smoking 51 1.4.2.1. Brief Overview 51 1.4.2.2. Smoking, Diabetes and Cardiovascular Disease 51 1.4.2.3. Smoking in Tonga and Pacific Countries 52 1.4.2.4. Smoking and Religion 53

1.4.3. Alcohol 54 1.4.3.1. Brief Overview 54 1.4.3.2. Alcohol, Diabetes and Cardiovascular Disease 54 1.4.3.3. Alcohol in Tonga and Pacific Countries 56 1.4.3.4. Alcohol and Culture 58

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CHAPTER 2 OBJECTIVES

2.1. Brief Overview 59 2.2. Objectives and Aims 59 2.3. My Role in the Study 60

CHAPTER 3 STUDY DESING AND METHODS

3.1. Brief Overview 61 3.2. Timing of Survey 61 3.3. Survey Team 62 3.4. Subject Selection 62 3.4.1. Exclusion Criteria 63 3.4.2. Household Contact 63 3.5. Promotion of the Survey 64 3.6. Survey Procedure 64 3.6.1. Staff Training 64 3.6.2. Data Collection 65 3.6.2.1. Registration 66 3.6.2.1.1. Demographic and Medical Characteristics 66 3.6.2.1.2. Smoking Status and Alcohol Consumption 66 3.6.2.1.3. Traditional Medicine 67 3.6.2.2. Anthropometric Measurements 67 3.6.2.2.1. Height Measurement 67 3.6.2.2.2. Weight Measurement 68 3.6.2.2.3. Body Mass Index 68 3.6.2.2.4. Circumference Measurement 68 3.6.2.2.5. Bioelectrical Impedance (BIA) 69 3.6.2.3. Clinical and Metabolic Measurement 70 3.6.2.3.1. Blood Pressure 70 3.6.2.3.2. Blood Glucose and HbA1c 70 3.6.2.3.3. Oral Glucose Tolerance Test 70 3.6.2.3.4. Blood Samples 71 3.6.2.4. Nutrition and Lifestyle Survey 71 3.6.2.4.1. Food Frequency Questionnaires 71

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3.6.2.4.2. Physical Activity 73 3.7. Data Analysis 74 3.7.1. Biochemical Analysis 74 3.7.2. Nutrient Analysis 75 3.7.3. Physical Activity Analysis 77 3.7.4. Statistical Analysis 78 3.7.4.1. Descriptive and Bivariate Analysis 78 3.8. Feedback to Participants 79

CHAPTER 4 RESULTS

4.1. Demographic Characteristics of Study Population 80 4.1.1. Age and Sex Characteristics 80 4.1.2. Geographic Location of study population 81 4.1.3. Occupation and Working Status of study population 81 4.1.4. Religious Distribution of study population 82

4.2. Characteristics of study population by Gender 83 4.2.1. Anthropometric Characteristics of study population by Gender 83 4.2.2. Clinical and Metabolic Characteristics of study population 84 by Gender 4.2.3. Nutrient Intake of study population by Gender 85 4.2.4. Lifestyle Behaviour of study population by Gender 86

4.3. Characteristics of study population by Age Group 87 4.3.1. Anthropometric Characteristics of study population by 87 Age Groups 4.3.2. Anthropometric Characteristics of study population by Age 88 and Gender 4.3.3. Clinical and Metabolic Characteristics of study population by Age 92 Groups 4.3.4. Clinical and Metabolic Characteristics by Age and Gender 93 4.3.5. Nutrient Intake of study population by Age Groups 94 4.3.6. Lifestyle Behaviours of study population by Age Groups 95

4.4. Characteristics of study population by Geographic Location 96 4.4.1. Anthropometric Characteristics of study population by 96 ix

Geographic Location 4.4.2. Clinical and Metabolic Characteristics of study population by 97 Geographic Location 4.4.3. Nutrient Intake of study population by Geographic Location 98 4.4.4. Lifestyle Behaviour of study population by Geographic Location 99

4.5. Characteristics of study population by Occupation 100 4.5.1. Anthropometric Characteristics of study population by Occupation 100 4.5.2. Clinical and Metabolic Characteristics of study population by 101 Occupation 4.5.3. Nutrient Intake of study population by Occupation 102 4.5.4. Lifestyle behaviour of study population by Occupation 103

4.6. Characteristics of study population by Religion 103 4.6.1. Anthropometric Characteristics of study population by Religion 104 4.6.2. Clinical and Metabolic Characteristics of study population by 104 Religion 4.6.3. Nutrient Intake of study population by Religion 105 4.6.4. Lifestyle behaviour of study population by Religion 106

4.7. Characteristics of study population by Glucose Tolerance 106 4.7.1. Anthropometric Characteristics of study population by Glucose 106 Tolerance 4.7.2. Clinical and Metabolic Characteristics of study population by 107 Glucose Tolerance 4.7.3. Nutrient Intake of study population by Glucose Tolerance 108 4.7.4. Lifestyle behaviour of study population by GlucoseTolerance 110

4.8. Prevalence of Overweight and Obesity 110 4.8.1. Prevalence of Overweight and Obesity by Age Groups 111 4.8.2. Prevalence of Overweight and Obesity by Location 112 4.8.3. Prevalence of Overweight and Obesity by Occupation 113 4.8.4. Prevalence of Overweight and Obesity by Religion 114

4.9. Characteristics by Body Mass Index 114 4.9.1. Anthropometric Characteristics by BMI 114 4.9.2. Clinical and Metabolic Characteristics by BMI 115 4.9.3. Nutrient Intake by BMI 116 4.9.4. Lifestyle behaviour by BMI 117

CHAPTER 5 DISCUSSION

5.1. The Study Population 119 5.2. Nutrient Intake 121 5.2.1. Overview 121 5.2.2. Total Calories 122 5.2.3. Protein Intake 123 5.2.4. Carbohydrate Intake 124 5.2.5. Dietary Fibre 126 5.2.6. Fat Intake 126 5.2.7. Alcohol 127 5.2.8. Physical Activity 128 5.3. Prevalence of Overweight and Obesity 130 5.4. Nutrient Intake and Glucose Tolerance 135

CHAPTER 6 SUMMARY 137

CHAPTER 7 STUDY LIMITATIONS 139

REFERENCE: 141

APPENDICES 168

Appendix I Survey Questionnaire

Appendix II Food Frequency Questionnaire

Appendix III Physical Activity Questionnaire

Appendix IV Food Items – Portion sizes and Frequency

Appendix V Recipes – Ingredients and amounts (Dignan et al. FAO 2004)

LIST OF FIGURES

Figure 1.1: Map of Tonga 2

Figure 4.1 Age-sex characteristics of study population 81

Figure 4.2 Body Mass Index of study population by age and gender 90

Figure 4.3 Weight of study population by age and gender 90

Figure 4.4 Waist circumference of study population by age and gender 91

Figure 4.5 Percentage of body fat of study population by age gender 91

Figure 4.6 Prevalence of overweight and obesity by age groups 112

Figure 4.7 Prevalence of overweight and obesity by location 113

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LIST OF TABLES

Table 1.1: Aetiological classification of diabetes mellitus (WHO, 1999) 10

Table 1.2: Comparison of Diabetes Complications among Tongans and 15 Australians after matching for age, gender and duration of diabetes

Table 1.3: Metabolic Syndrome Definition (IDF, 2005) 17

Table 1.4: BMI Classification – WHO, 1998 19

Table 1.5: BMI Classification – Bennett, 1979 20

Table 1.6: Comparison of Prevalence of Overweight and Obesity in males 25

and females according to BMI classification in the 1986

National Nutrition Survey and the 1992 Non-Communicable

Diseases Survey in Tonga Table 1.7: Comparison of body size by BMI in males and females in 26 the Nutrition Survey, 1986 and 1992 in Tonga

Table 1.8: Three food groups with food classified as local or imported food 33

Table 3.1: Values for diagnosis of diabetes mellitus and other categories 75

of hyperglycaemia

Table 4.1: Age and sex characteristics of study population 80

Table 4.2 Demographic characteristics of study population 82

Table 4.3: Anthropometric characteristics of study population by gender 84

Table 4.4: Clinical and metabolic characteristics of study population by 85 gender Table 4.5: Nutrient intake of study population by gender 86

Table 4.6: Lifestyle behaviour of study population by gender 87

Table 4.7: Anthropometric characteristics of study population by age 88

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groups

Table 4.8: Age specific anthropometric characteristics of study population 89 by gender

Table 4.9: Clinical and metabolic characteristics of study population by 92 age groups Table 4.10: Clinical and metabolic characteristics of study population 93 by age and gender Table 4.11: Nutrient Intake of study population by age groups 95

Table 4.12: Lifestyle behaviour of study population by age groups 96

Table 4.13: Anthropometric characteristics of study population by 97 geographical location Table 4.14: Clinical and metabolic characteristics of study population by 98 geographic location

Table 4.15: Nutrient Intake of study population by geographical location 99

Table 4.16: Lifestyle behaviour of study population by geograph location 100

Table 4.17 Anthropometric characteristics of study population by occupation 101

Table 4.18 Clinical and metabolic characteristics of study population by 101 occupation Table 4.19 Nutrient Intake of study population by occupation 102

Table 4.20: Lifestyle behaviour of study population by occupation 103

Table 4.21: Anthropometric characteristics of study population by religion 104

Table 4.22: Clinical and metabolic characteristics of study population by 105 religion Table 4.23: Nutrient Intake of study population by religion 105

Table 4.24: Lifestyle characteristics of study population by religion 106

Table 4.25: Anthropometric characteristics of study population by 107 glucose tolerance Table 4.26: Clinical and metabolic characteristics of study population by 108 glucose tolerance

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Table 4.27: Nutrient Intake of study population by glucose tolerance 109

Table 4.28: Lifestyle behavious of study population by glucose tolerance 110

Table 4.29: Prevalence of overweight and obesity by age groups 111

Table 4.30: Prevalence of overweight and obesity by geographic location 112

Table 4.31: Prevalence of overweight and obesity by occupation 113

Table 4.32: Prevalence of overweight and obesity by religion 114

Table 4.33: Anthropometric characteristics of study population by BMI 115

Table 4.34: Clinical and metabolic characteristics of study population by BMI 116

Table 4.35: Nutrient Intake of study population by BMI 117

Table 4.36: Lifestyle behaviour of study population by BMI 118

Table 5.1: Comparison of the New Zealand Taskforce Target Values and 121 the Australian Recommended Dietary Intake (RDI) with the Study Population Mean Intake Table 5.2: Comparison of the prevalence of overweigh and obesity 131 according to the BMI classification used in the 1986 National Nutrition Survey and the 1992 NCD survey in Tonga

CERTIFICATE OF ORIGINALITY

“I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, nor material which to a substantial extent has been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis.

I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project‟s design and conception or in style, presentation and linguistic expression is acknowledged”.

(Signed) …………………………………………………..

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GLOSSARY OF ACRONYMS

System International Units and standard abbreviations have been used throughout. ADA American Diabetes Association

ANOVA Analysis of variance

ANCOVA Analysis of Covariance

BIA Bioimpedance Analysis

BMI Body Mass Index, kg/m2

%BF Percentage Body Fat

BF Body Fat, % cal Calorie

CHO Carbohydrate

CVD Cardiovascular Diseases

Cm Centimetres

F Female

FFQ Food frequency questionnaire g gram g/d gram per day

HDL High density lipoprotein ht Height, cm kcal Kilocalories kg Kilograme

L Litre

LDL Low density lipoprotein m Male xvii

mg milligram mm milimetre mmol/L millimoles per litre mmHg millimeters of mercury

MUFA Monounsaturated fatty acid n Number in sample

NCD Non-communicable disease

NIDDM Non-insulin dependent diabetes mellitus p Probability

PA Physical Activity

PUFA Polyunsaturated fatty acids

SAF Saturated fatty acids

SE Standard error

SD Standard deviation

SPC South Pacific Commission or Secretariat for Pacific Countries

TG Triglycecides

WHO World Health Organisaiton

WHR Waist to hip ratio wt Weight,kg

Y Year

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CHAPTER 1

1. INTRODUCTION

1.1 About Tonga : The Land and it’s People

1.1.1 Geography

The Kingdom of Tonga is an independent island nation situated in the central South Pacific, scattered between latitudes 15o and 23o South and longitudes 173o and 176o West (Figure 1). The Kingdom consists of 171 islands, 41 of which are inhabited, with a total land area of 750 sq km spread over 360,000 sq km of the ocean. There are three main island groups in Tonga. The largest (260 sq km) and by far the most populous island is Tongatapu in the south and it includes the capital Nuku‟alofa. The Ha'apai island group is just north of Tongatapu and consists of numerous small and relatively isolated islands. The Vava‟u island group is in the north and also consists of a number of islands (Bonapace et al., 1995)

Most of the eastern islands including Tongatapu are low lying and of coral formation, although several, especially to the west, are of volcanic origin. The volcanic ash creates fertile soil in these islands, however because of their inaccessibility, they are the least cultivated. The limestone islands have sandier soils but suffer exhaustion under constant cropping.

There are two distinct seasons in Tonga, the warm wet season from December to April and the cool dry season from May to November. Most rainfall occurs during the warm season when both temperature and humidity are high, which roughly coincides with the cyclone season. Cyclones occur every few years and can be quite destructive. The average temperature is 230C and Tonga has an average rainfall of 1610 mm per year. Although the islands lie within the tropics, the climate, especially in the southern group, is moderately temperate. 1

Figure 1.1 : Map of Tonga

There is insufficient surface water on several islands, and agriculture is rain fed and subject to occasional droughts. Tonga is predominantly an agricultural country and about 50 percent of the population works predominantly in the subsistence sector and is

economically dependant on agricultural exports. Pumpkin, coconut, coconut products and vanilla are the major sources of cash income. Domestic animals include horses, cattle, pigs and chickens. Marine life is abundant and provides an important source of food. The fishing industry is developing and concentrating largely on reef fishing and is geared to meet subsistence needs. Commercial deep sea fishing, especially long line tuna fishing, is established as a source of income for many people as well as contributing to the economy. Seaweed farming for the Japanese market is very popular.

1.1.2 Population

The 1996 Tonga Census (Statistics Dept, 1999) recorded 97,784 people living in Tonga, giving the Kingdom an overall population density of about 141 persons per sq km. The population is unevenly distributed, with 68.5 per cent living on Tongatapu including 20% of the total population residing in the capital city of Nuku'alofa. Sixteen percent live in Vava'u, and 8.3 per cent in Ha‟apai and the remainder scattered in the smaller islands of „Eua and the Niua group.

The overall population growth rate is stable at 0.3 percent per annum due to overseas migration. A significant number of people have migrated overseas in the last few decades, an annual net migration rate of 17.5 per thousand. About 100,000 Tongans are living in Australia, New Zealand and the United States.

In terms of age structure, Tonga is classified as a young population with a median age of 19.9 years with nearly half (45%) being children under the age of 15 years.

Education is free and compulsory for children from the ages of 6 to 14. Most primary schools are operated by the government, while most secondary schools are sponsored by churches. Further education, especially tertiary, can be pursued overseas in either New Zealand, Australia or in neighbouring Pacific Islands. The University of the South Pacific has established a centre in Tongatapu and the „Atenisi Institute (1971), a private Tongan institution that offers several degree programs, is located in Nuku‟alofa to cater for those students who wish to continue their education without leaving the island.

Tonga‟s educational indicators are among the highest in the Pacific with adult literacy rates of nearly 100 percent.

1.1.3 History and Culture

Tongans are Polynesians and probably came from the islands of Southeast Asia, around the second millennium. Tonga developed as a highly stratified society with social classes and paramount chiefs. In 1616 Dutch explorers became the first Europeans to visit Tonga. British explorer Captain Cook came three times between 1773 and 1777. He named Tonga the Friendly Islands, due to the kind and friendly welcome he received from the indigenous people. Most of the population is Tongan with less than two percent consisting of members of other ethnic groups which include Europeans, Asians and Pacific Islanders (mainly Fijians and Indians).

Tonga is a hereditary constitutional monarchy and is the only surviving kingdom in the Pacific (Campbell, 1992). It has been a British Protected State since 1900 and Great Britain had great influence over the Kingdom‟s foreign policy. Tonga has never been formally colonized. King Taufa‟ahau Tupou V is the present head of the state. The Privy Council, which is headed by the king and includes the cabinet ministers, is the highest executive body.

Tonga has retained much of its Polynesian culture. There is respect for traditional authority and customs, and the lifestyle is conservative. Tonga's population has been almost entirely Christian for more than 100 years. Christianity has been thoroughly integrated into Tongan society. All commerce and public entertainment are prohibited on Sundays, the Christian day of prayer and rest, and much of Tongan social life is structured around the church.

The majority of Tongans (41.3 percent) belong to the Free Wesleyan Church which is headed by Tonga‟s monarch. Roman Catholic, Latter Day Saints, Free Church of Tonga, the Church of Tonga and other Christian denominations are minority religions.

Tonga has a unique family value based on the well-being of the extended family, which typically includes parents, siblings, grandparents, aunts, uncles, and cousins. Men head the extended family, while women typically play supportive roles.

The indigenous language is Tongan, a Polynesian tongue closely related to Samoan and Nieuan. English and Tongan are the official languages. Tongan is preferred for everyday communications while English, which is taught as a second language in schools, is used mainly for business.

1.1.4 Infrastructure

An international airport is located at Fua‟amotu, 21 km from Nuku‟alofa. Domestic air travel from Tongatapu to „Eua, Ha‟apai, Vava‟u, Niuatoputapu, and Niuafo‟ou islands is provided by Fiji Air. With the exception of Tongatapu and Vava‟u, the islands have unpaved runways that can only accommodate small craft. Several airlines, including Air New Zealand and Pacific/Virgin Blue Airlines, provide frequent international flights to Fiji, Samoa, New Zealand, Australia, and the United States.

During the reign of King Taufa‟ahau Tupou IV, the country became increasingly connected to regional and international networks. Up to and including the last decade of the 19th Century, Tonga was a regional power and had extensive trading and political relations with Fiji and Samoa. Contemporary regional infrastructure development has maintained these links, and includes others as well. Most importantly, active networks move people and material between Tonga and New Zealand, Australia and the United States. New Zealand is the country‟s largest trading partner, but the United States has become increasingly important as the Tongan migrant communities in that country have grown.

Tonga has its own wharf that can accommodate large ships. Tongatapu and most of the islands of Vava‟u have good infrastructural links, but most of the Ha‟apai group and some of the more isolated areas of Vava‟u have limited access to communication infrastructure. Several cargo ships a month service the island bringing in imported goods (including food such as mutton flaps, beef, poultry, frozen vegetables, canned or 5

tinned fruits and vegetables) and taking agriculture and fish products for the exports market in New Zealand, Australia, Japan and other Pacific Islands.

Small retail outlets supplying imported foods can be found in almost every Tongan village. On the main islands, where electricity is available, these outlets (and some large wholesalers) carry canned and frozen foods. People residing on smaller outer islands may not have direct access to frozen foods, but travel to larger centres to purchase supplies. Outside of the urban and peri-urban areas of Nuku‟alofa on Tongatapu and Neiafu in Vava‟u subsistence agriculture and subsistence marine use continue to provide most of the foods consumed, although imported foods (either canned or dried) are available everywhere.

1.1.5 Health Status in Tonga

The health indicators for Tonga are generally good. The life expectancy at birth for a male is 69 years, and for a female is 70 years. This reflects improved maternal child health and the high level control of infectious and communicable diseases in Tonga. The adult population however is increasingly threatened by the alarming growth in Non- communicable Diseases (NCD), which has the potential to eventually lead to a lowering in life expectancy.

1.1.5.1 Mortality and Morbidity Rates in Tonga

There has been a marked increase in NCDs in the last two to three decades. Hospitalisation records provide some information on this, although the limitations of these data are acknowledged. In the period 1956-1960, only 8% of all patients who died in hospital in Tonga had a diagnosis of cancer or cardiovascular diseases. However, in the period 1976-1980 this figure increased to 44% of hospital deaths, and the 1988 statistics show deaths from cardiovascular diseases represent over 30% of all deaths.

Hospital records also show continuing increases in admissions for type 2 diabetes and diabetes complications. An alarming high rate of diabetes related amputations was reported at the 50th Tonga Medical Association Conference in 1992, highlighting

increases over the previous 5 years from an average of 12 to 15 amputations per year (Tangi, 1992). Also diabetes complications at diagnosis are common (Mafi, 1992).

In 1999, 20% of admissions to the surgical ward were related to diabetes sepsis. Even more importantly, diabetic sepsis was directly involved in 45% of in-patient deaths (Tonga Ministry of Health, 2000).

Between 1995 and 2004, the leading causes of death in Tonga were diseases of the cardiovascular system with the 5 leading causes of death reflecting the shifting patterns of mortality from communicable diseases to non-communicable diseases (Tonga Ministry of Health, 2005)

1.2 Diabetes and Non-communicable Diseases

1.2.1 Diabetes Mellitus

1.2.1.1 Definition

The term diabetes mellitus describes a metabolic disorder of multiple aetiology characterized by chronic hyperglycaemia with disturbances of carbohydrate, fat and protein metabolism resulting from defects in insulin action and/or insulin production from the pancreas (WHO, 1999).

With decreased insulin action and / or production, the body is unable to utilise glucose that is ingested or released by the liver. As a result blood glucose rises above normal and results in hyperglycaemia. This can lead to excessive urination, thirst, blurring of vision and weight loss, which are symptoms of diabetes. In it‟s most severe forms, if left untreated, marked hyperglycaemia develops which can result in a non-ketotic hyperosmolar state or the hyperglycaemia may be accompanied by a breakdown of body fat leading to ketoacidosis. Both of these states may lead to coma and in the absence of effective treatment, death (Hampson, 1998; WHO, 1999). More commonly in type 2 diabetes, symptoms are not severe, or may be absent, and consequently hyperglycaemia sufficient to cause pathological and functional changes may be present for a long time 7

before the diagnosis is made. The long term effects of diabetes mellitus include progressive development of the specific complications of retinopathy with potential visual loss and blindness, nephropathy that may lead to renal failure, and neuropathy with risk of foot ulcers, amputation, Charcot joints, or autonomic dysfunction, including sexual dysfunction (WHO, 1999). People with diabetes are at increased risk of cardiovascular, peripheral vascular and cerebrovascular disease which result from a combination of hyperglycaemia, lipid abnormalities and elevated blood pressure (Hiller et al., 1988; Stamler et al., 1993; Haffner et al., 1998; Diabetes Control and Complications Trial, 1993; Morrish et al., 1991; WHO, 1999).

1.2.1.2 Classification

There are three main types of diabetes mellitus: Type 1, Type 2 and Gestational Diabetes Mellitus (GDM) (WHO, 1999; American Diabetes Association, 1997). The WHO (1999) aetiological classification of diabetes is presented in Table 1.1. It encompasses both clinical stages and aetiological types of diabetes mellitus and other categories of hyperglycaemia.

1.2.1.2.1 Type 1 Diabetes

Type 1 diabetes results from destruction of the insulin-producing beta-cell of the pancreas and insulin treatment is required for survival and to prevent the development of ketoacidosis, coma and death (WHO, 1999). It is an autoimmune disease in which the body‟s immune system reacts against and destroys the insulin-producing beta cells in the islets of the pancreas resulting in an absolute deficiency of insulin. Type 1 diabetes is usually characterized by the presence of anti-GAD, islet cell or insulin antibodies which identify the autoimmune processes that lead to beta-cell destruction. This destruction involves abnormal regulation of the immune response due to one or more defects (Flier, 1992; WHO, 1999).

1.2.1.2.2 Type 2 Diabetes

Type 2 Diabetes is the most common form of diabetes and is characterised by disorders of insulin action and/or insulin secretion due to defects in both beta-cell function and the target cell response to insulin (WHO, 1999). This results in varying degrees of insulin resistance and an inadequate compensatory insulin secretion (Cerveny et al., 1998). Both are usually present at the time that this form of diabetes is clinically manifest. The specific reasons for the development of these abnormalities are not yet known (WHO, 1999).

1.2.1.2.3 Gestational Diabetes Mellitus (GDM)

Gestational diabetes is carbohydrate intolerance resulting in hyperglycaemia of variable severity with onset or first diagnosis during pregnancy. This is one of the most common complications of pregnancy. It does not exclude the possibility that the glucose intolerance may antedate pregnancy but has been previously unrecognized. While the carbohydrate tolerance usually returns to normal in the immediate postpartum period, there is a significant chance of the subsequent development of permanent diabetes in the mother, and an increased chance of the baby developing obesity and impaired glucose intolerance and/or diabetes later in life The definition applies irrespective of whether or not insulin is used for treatment or the condition persists after pregnancy (WHO, 1999; ADA, 1997).

1.2.1.2.4 Other Specific Types

Other specific types are less common causes of diabetes mellitus, but are those in which the underlying defect or disease process can be identified in a relatively specific manner. They include, for example, fibrocalculous pancreatopathy, diabetes resulting from pancreatitis, pancreatic carcinoma, cystic fibrosis and haemochromatosis which damage the beta cells and impair insulin secretion. Other endocrine disorders such as Cushing‟s Syndrome, Glucagonoma, diabetes resulting from excess secretion of several hormones that antagonize insulin action (WHO, 1999; ADA, 1997; Yajnik et al., 1992).

1.2.1.2.5 Impaired Glucose Regulation – Impaired Glucose Tolerance (IGT) and Impaired Fasting Glycaemia (IFG)

Impaired glucose regulation (IGT and IFG) refers to a metabolic state intermediate between normal glucose homeostasis and diabetes. IFG and IGT are not interchangeable and represent different abnormalities of glucose regulation, one in the fasting state and the other post-prandial. IGT refers to 2-h post glucose challenge plasma glucose level lower than used to define diabetes but higher than considered normal. IFG refers to fasting glucose concentrations which are lower than required to diagnose diabetes mellitus but higher than the normal reference range. Both IGT and IFG are considered stages in the natural history of disordered carbohydrate metabolism. People with IGT or IFG have an increased risk of progressing to diabetes and developing macrovascular disease. IGT and IFG are not disease entities in their own right, but rather risk categories for future diabetes and/or cardiovascular disease (WHO, 1999).

Table 1.1: Aetiological classification of diabetes mellitus (WHO, 1999)

Type 1 (beta-cell destruction, usually leading to insulin deficiency) Autoimmune Idiopathic Type 2 (may range from predominantly insulin resistance with relative insulin deficiency to a predominantly secretory defect with or without insulin resistance) Gestational diabetes mellitus (GDM) Other specific types Genetic defects of beta-cell function Genetic defects in insulin action Disease of the exocrine pancreas Endocrinopathies Drug- or chemical-induced Infections Uncommon forms of immune-mediated diabetes Other genetic syndromes sometimes associated with diabetes

1.2.2 Diabetes and Cardiovascular Diseases (CVD) in Tonga and in the Pacific Countries

1.2.2.1 Brief Overview

Diabetes mellitus, cardiovascular disease and hypertension were not evident among the Pacific Island nations until contact with Europeans during the 1800s. The earliest accounts of health status in the islands, recorded by missionaries and sailors visiting the region, describe healthy, strong and robust people who were largely free from disease. The most common causes of death were food shortages, created by war or storms, and the severe effects of disease such as influenza and whooping cough brought in from the outside (McArthur, 1967).

As western countries pattern of living and eating became more common in many Pacific countries, the major causes of death shifted from these communicable diseases to NCDs. Several population-based surveys have illustrated the magnitude of this problem and suggested that changes from a traditional to a modern way of life have enhanced the development of NCD (Prior 1971; Zimmet et al., 1981; Hoskins et al., 1987; King et al., 1988; Taylor et al., 1985; King et al., 1989; Taylor et al., 1991; World Bank, 1994). It is hypothesised that these lifestyle changes interacted with genetic factors, which in the past favoured fat storage so that people could survive food shortages but which today have become a disadvantage because they lead to overweight in the presence of an abundant supply of food (Swinburn,1995).

The degree of modernisation varies widely throughout the Pacific and this is reflected in mortality patterns from NCD (Taylor et al., 1989). Unfortunately, recent mortality data are sparse but an increase in diabetes prevalence has been reported in many countries (Collins et al., 1994; Amos et al., 1997; WHO. 1998; Coyne, 1984). Since most people with diabetes die of heart disease (Jarrett et al., 1982) further increases in coronary heart disease can be expected.

It is projected that NCDs will be the main cause of 7 out of every 10 deaths in developing countries by the year 2020 (Khor, 2001). Diabetes and CVD are major causes of premature deaths, morbidity and disability in most of these countries.

In 1999, CVD contributed to one third of the 17 million global deaths of which 78% occurred in low and middle-income countries. It is estimated that CVD will become the leading cause of death in developing countries by 2010 (WHO, 2001)

In 2000, it was estimated that there were 171 million people in the world with diabetes. It is projected to increase to 366 million by the year 2030 (Wild et al., 2004).

Mortality statistics due to CVD account for almost 50% of all deaths in both developing and developed countries and premature mortality occur two and half times more in men than women. It is also estimated that in the developing regions of Africa, Western Asia and Southeast Asia, 15–20% of annual deaths are due to CVD, equivalent to 3-4 million deaths, or about 70% more than for developed countries (BHF, 1992)

New Zealand, Australia, Singapore, Western Samoa and urban areas of China are classified in the „high mortality‟ from CVD category, according to the proportion of total deaths from all causes. These countries represent a rate in excess of 30-35% of total deaths in the population due to CVD (Khor, 2001).

Mortality statistics between 1987 and 1991 in New Zealand showed Pacific Island males of all ages accounted for 51% of deaths from CVD whilst Pacific Island females accounted for 44% (Bathgate et al., 1994).

1.2.2.2 Diabetes Prevalence in the Pacific Countries

Diabetes is one of the major chronic diseases among Pacific people and it is a serious and growing health problem through out the world (Wild et al., 2004). It is estimated that there are currently 30 million people in the Western Pacific Region with diabetes and that by 2025 this number will have increased to at least 55 million (WHO, 2000).

Diabetes prevalence in the Pacific is among the highest rates in the world. A background paper presented at the recent Meeting of Ministers of Health for the Pacific Island countries (WHO, 2003) reported the rates of diabetes in the Pacific range from 10% to 40% for different population groups.

In New Zealand, the prevalence of type 2 diabetes among the Pacific Island population is relatively high, coinciding with the increasing prevalence of overweight and obesity (NZ Ministry of Health, 2001). The 1996/97 Health Survey found that around 3.7% (1 in 27 adults) of the New Zealand population reported having diabetes (NZ Ministry of Health, 1999). The prevalence of diagnosed diabetes is higher among Maori (5-10%) and Pacific Island adults (4 -8%) than among New Zealand Europeans (3%) and people of Asian origin (4%) (NZ Ministry of Health, 1999). There are also higher rates of gestational diabetes in Pacific women than in other New Zealanders (Bathgate et al. 1994).

In 2000, the estimated number of people in New Zealand with known diabetes was 115, 000, and predicted to increase to over 160, 000 by 2021 (NZ Funding Authority, 2000). Diabetes New Zealand reported that there may be more than 50,000 people with undiagnosed diabetes in New Zealand and more than 300,000 with impaired glucose tolerance (www.diabetes.org.nz).

Epidemiological studies over the past 30 years in many Pacific Islands show large variations in the prevalence of diabetes, although some of these surveys were done many years ago and almost certainly do not reflect current rates of diabetes. Reported rates range from zero in the highlands of Papua New Guinea (King et al., 1985) and rural Vanuatu (Carlot-Tary et al., 1999) to close to 30% in Nauru (Coughlan et al., 1997), and the urban community of Koki in Port Moresby, Papua New Guinea (Dowse et al., 1994).

The number of cases of diabetes is expected to increase substantially in the future as the Pacific population ages and especially if behaviours that encourage the onset of diabetes do not change (Harris et al., 1993).

1.2.2.3 Diabetes Prevalence in Tonga.

The first diabetes prevalence study in Tonga was carried out by Finau and co-workers in 1973 (Finau et al., 1982). They found a crude prevalence rate of 5.3% in adults, with higher rates in women than in men. This study involved a total of 794 people from three areas, in urban Nuku‟alofa and two rural areas in Ha‟apai (Lotofoa and Faleloa). The age adjusted prevalence rates for diabetes were 5.5% (urban) and 4.7% (rural) in men and 9.7% (urban) and 10.1% (rural) in women, indicating similar prevalence in urban and rural areas. The diagnosis of diabetes was based on a plasma glucose level of ≥ 10.0 mmol/l two hours following a 75g glucose load, which is at variance with the WHO criteria (1999) and which would now include both diabetes mellitus and some subjects with IGT.

Non-communicable diseases and nutrition surveys conducted in Tonga in 1992 (Foley et al., 1998) included 950 people aged 14 to 70 years. Participants were interviewed about their personal medical history and diabetes was reported by 1.6% of the participants, with the same proportions in rural and urban areas, and higher in women, 2.3% than in men, 0.8%. Prevalence of diabetes was higher (2.8%) in the older age groups (over 34 years) and only 0.2% in those less than 34 years for both men and women. It is likely that these proportions are a significant underestimation of the true prevalence in the Kingdom as the participants without known diabetes were not screened for diabetes.

The first population-based epidemiological study that used the WHO (1999) diagnostic criteria to determine diabetes prevalence was conducted by the Ministry of Health, Tonga and Prince of Wales Hospital, Sydney in 1998 and 2000 (Colagiuri et.al., 2002) . The survey included 1024 people aged ≥ 15 years from Tongatapu (608 participants), Ha‟apai (214 participants) and Vava‟u ( 202 participants). The age and sex standardized prevalence of diabetes was 15.1%. The diabetes prevalence rate in women was higher than in men (17.6 vs 12.2%), but this difference was not significant. Prevalence was slightly higher but not significantly difference in Vava‟u/Ha‟apai than Tongatapu (11.3 vs 9.7%). Prevalence of diabetes was higher in the older age groups, approximately 20% in people over 50 years of age. This study indicated that the prevalence of diabetes had 14

doubled since 1973 and almost another estimated 20% of the population has lesser degrees of glucose intolerance.

1.2.2.4 Prevalence of diabetes complications in Tonga

Diabetes complications are a burden to the Tongan Health Services. In 1995, one hundred and ninety five people with type 2 diabetes attending the Vaiola Hospital Diabetes clinic were assessed for metabolic status and presence of diabetic complications and compared with an equivalent Australian sample attending the Diabetes Centre at the Prince of Wales Hospital, Sydney (Colagiuri et al., 1999; Palu et al., 2000). Details of the results are presented in Table 1.2. The Tongans in this study had considerably worse diabetes control than their Australian counterparts (HbA1c 9.8% v 8.1%), with at least twice the rate of retinopathy, and signs of early kidney disease, and seven times the rate of amputation.

Table 1.2: Comparison of Diabetes Complications among Tongans and Australians after matching for age, gender and duration of diabetes

Non-Tongan Tongan HbA1c (%) 8.1 9.8 Blind (%) 1.4 7.2 Retinopathy (%) 21.3 41.6 Neuropathy (%) 16.4 30.2 Foot Ulcer (%) 1.1 4.4 Amputation (%) 0 7.8 Microalbumiura (%) 33.9 62.5

1.2.3 Risk Factors for Diabetes and Cardiovascular Disease

1.2.3.1 Brief Overview

Diabetes and cardiovascular disease are multifactorial metabolic disorders and are often part of a wider metabolic syndrome where risk factors for both diseases are present such as hyperglycaemia, hyperinsulinaemia, obesity, hypertension and lipid abnormalities (WHO, 1980; Hodge et al., 1994). Genetic predisposition has been identified both in 15

type 1 and in type 2 diabetes (Cowie et al., 1993; Hafner, 1998). Also some environmental risk factors like physical inactivity (Manson et al., 1991, Manson et al., 1992, Perry et al., 1995), dietary habits and physiological stress are recognized (King et al. 1988; Zimmet et al., 1983; Cowie et al., 1993; Erikson et al., 1991).

Although interaction between genetic and environmental factors is strongly suspected, much controversy remains regarding the degree and intensity with which the various environmental factors influence diabetes development and progression in different ethnic groups. Possibly, the susceptibility to the known environmental factors differs among different ethnic groups (Cowie et al., 1993). But the exact role played by these factors in the pathogenesis is not known (Zimmet et al., 1983; WHO, 1980). This may explain the variation in diabetes prevalence between populations (Zimmet et al., 1983; WHO, 1980; Cowie et al., 1993; Eriksson et al., 1991). A number of investigators have suggested that environmental factors rather than genes are the main determinants of diabetes prevalence (King et al., 1988; Mbanya et al., 1999).

1.2.3.2 The Metabolic Syndrome

Insulin-resistant subjects who are able to sustain the degree of compensatory hyperinsulinaemia necessary to maintain near-normal glucose homestasis are at risk of developing a cluster of additional abnormalities, all of which increase the risk of cardiovascular disease. This cluster of metabolic abnormalities is known as Syndrome X, the Insulin Resistance Syndrome, or Metabolic Syndrome (Reaven, 1997; Zimmet, 1992) with the most popular terminology being the metabolic syndrome (Eckel et al., 2005). The ultimate importance of the metabolic syndrome is that it helps identify individuals at high risk of developing type 2 diabetes and cardiovascular disease.

The cause of the syndrome remains obscure, and a number of expert groups have proposed definitions and diagnostic criteria. The WHO diabetes group in 1999 proposed criteria that had insulin resistance, impaired glucose tolerance or diabetes with at least two CVD risk factors: raised blood pressure, hypertriglyceridaemia and/or low HDL-

cholesterol, obesity (as measured by waist to hip ratio or body mass index) and micrroalbuminuria.

The European Group for the Study of Insulin Resistance (Balkau et al., 1999) suggested a modification of the WHO definition by having hyperinsulinaemia as the basic requirement, excluding people with diabetes and having waist circumference (with different cut offs) as the measure for obesity.

In 2001, the US National Cholesterol Education Program: Adult Treatment Panel III proposed a definition which required the presence of any three of five components : central obesity, raised blood pressure, raised triglycerides, low HDL-cholesterol, and fasting hyperglycaemia.

The International Diabetes Federation (IDF) (2005) recently proposed one practical definition that would be useful for any country for the identification of people with the metabolic syndrome (Table 1.3). This definition would also allow comparative long- term studies, which could then be used, if necessary, to refine the definition on the basis of solid endpoints.

Table 1.3: Metabolic Syndrome Definition (IDF, 2005)

Central Obesity Waist circumference – ethnicity specific Plus any two: Raised triglycerides Reduced HDL-cholesterol (1.03 mmol/L in men and 1.29 mmol/L in women) Raised blood pressure (systolic ≥ 130 mm/Hg, diastolic ≥ 85 mm Hg) Raised fasting plasma glucose Previously diagnosed type 2 diabetes

It has been hypothesized, that insulin resistance in an essential and possibly mediating part of this collection of undesirable metabolic abnormalities. Individuals with insulin resistance tend to be obese with a central body fat distribution. However, it is not clear whether obesity causes insulin resistance, or insulin resistance causes obesity, or the two arise separately from a common factor (Jensen et al., 2000). Much of the research

supports the hypothesis that obesity, especially abdominal obesity, contributes to insulin resistance. Emerging data suggest that insulin resistance and obesity could arise simultaneously as a result of independent genetic and environmental factors.

1.2.3.3 Overweight and Obesity

1.2.3.3.1 Brief Overview

Obesity has been defined as a disease in which excess body fat has accumulated to such an extent that health can be harmfully affected (WHO, 2000). It is a consequence of an energy imbalance where energy intake exceeds energy expenditure over an extended period of time. The aetiology of obesity is considered a complex interplay between genetic, social, economic, and cultural factors. Hill (1998) describes the aetiology as an interaction between the environment and a person‟s genes. Prentice and Jebb (1995) and Kaplan (1996) suggest multifactoral causes, ultimately determined by the long-term imbalance of energy intake and expenditure, which themselves may be genetically controlled.

Obesity has been identified by the World Health Organisation as the single most important risk factor in the development of type 2 diabetes and cardiovascular disease (WHO,1985). A positive association between obesity and the risk of developing type 2 diabetes has been repeatedly observed in both cross-sectional (Hartz et al., 1983; Haffner et al., 1987; van Noord et al., 1990; Dowse et al., 1991; McKeigue et al., 1992; Shanten et al., 1993; Collins et al., 1994) and prospective studies ( Ohlson et al., 1985; Modan et al., 1986; Colditz et al., 1990; Haffner et al., 1990; Cassano et al., 1992; Charles et al., 1991). There is strong evidence from well designed longitudinal studies that obesity in adult life increases the risk of type 2 diabetes particularly in men and it increases proportionately with increasing BMI. Women with excess weight gain of 8.0 to 10.9 kilograms are 2.7 times more at risk compared with those of stable weight (Colditz et al., 1995).

1.2.3.3.2 Body Mass Index (BMI)

The operational definition of obesity and overweight is based on body mass index (BMI), a frequently used measure when assessing weight at both the population and the individual level (Prentice et al., 2001; Stamler, 1993; NHMRC, 1997; WHO, 1997). It is also used to define health risk including risk of mortality and is significantly correlated with percentage body fat (Roche et al, 1981).

BMI is defined as the ratio of body weight (kg) divided by height (m2). In adults, the BMI cut-off values to classify overweight and obesity recommended by WHO (1998) is as follows (Table 1.4).

Table 1.4: BMI Classification (WHO, 1998)

Classification BMI (kg/m2) Risk of co-morbidities

Underweight < 18.5 Low Normal 18.5 – 24.9 Average Overweight > 25 Pre-Obese 25 – 29.9 Increased Grade 1 Obesity 30 – 34.9 Moderate Grade 2 Obesity 35 – 39.9 Severe Grade 3 Obesity > 40 Very Severe

According to a WHO expert consultation (2003), the WHO BMI classification for overweight and obesity are intended for international use. Overweight and obese persons are considered at risk of developing associated morbidities or diseases such as hypertension, high blood cholesterol, type 2 diabetes, coronary heart disease and other diseases (Expert Panel on the Identification, Evaluation, and Treatment of Overweight in Adults, 1998).

Early studies conducted in the Pacific countries used different criteria to classify overweight and obesity (Connie et al., 2000). The levels of BMI roughly corresponded to the Metropolitan Life „Ideal‟ Body Weight tables (Bennett, 1979) as presented in Table 1.5.

Table 1.5: BMI Classification (Bennett, 1979)

Ideal Body Weight BMI (%) Males Females Overweight (moderate obesity) 120 – 139 % 27 – 31 25 – 30 Obesity (marked obesity) ≥ 140% ≥ 32 ≥ 30

Higher cut-offs may be more appropriate for defining overweight and obesity in Pacific Island populations. The South Pacific Commission has suggested that two BMI units are added to the cut-offs recommended by the WHO (1997). Overweight is therefore defined as a BMI between 27.1 – 32 kg/m2, and obese as a BMI ≥ 32 kg/m2. These higher cut-offs are based on the assumption that Pacific Islands people are more muscular than Caucasians. This has subsequently been supported by body composition evidence (Swinburn et al., 1996; Rush et al., 1997).

1.2.3.3.3 Waist Circumferences and Waist to Hip Ratio

Other measurement tools used to assess overweight and obesity include waist circumference. This is a simple and convenient measurement that closely correlates with BMI and is unrelated to height (WHO, 1997). It is a recognized indicator of intra- abdominal fat and total body fat (Taylor et al., 2000; Despres et al., 2001; Antipatis et al., 2000). Increase in waist circumference is also indicative of increased risk of cardiovascular and other chronic diseases (Lean et al., 1998; Han et al., 1998).

The distribution of fat is considered to be more closely related to the major cardiovascular and metabolic health risk associated with body composition than high levels of fat or excess weight (Wilson et al., 2001). Central obesity is recognized as a significant precursor of hyperinsulinaemia, increased plasma triglycerides, decreased HDL levels and elevated blood pressure as well as increased morbidity and premature mortality (Despres et al., 1990; Bjorntorp, 1997).

An increased abdominal girth is associated with a number of chronic diseases which lower overall „quality of life‟. Lean et al., (1998) studied the effect of increased waist circumference on prevalence of respiratory difficulties, type 2 diabetes and CVD and found that subjects with increased waist circumference had a higher prevalence of chronic diseases.

Waist to hip ratio (WHR) was introduced by Kiotkeiwski et al (1983) as another way of determining risk apart from waist circumference alone. WHR has been used extensively as an indicator of abdominal obesity in adult population studies which show that subjects with an increased WHR are more likely to develop metabolic complications of obesity such as hypertension and hyperinsulinaemia (Seidell et al., 2001).

WHR has been identified as a robust measure of risk in many population studies. In an European population, a WHR > 1.0 for men and > 0.85 for women is used to identify those with excess abdominal fat accumulation and a higher risk (Caterson, 2002; Seidell et al., 2001; Han et al., 1997)

The use of WHR has limitations due to ethnic or racial differences. Marcus et al (1998) observed that because African-Americans have smaller hips than Caucasian-Americans, they tend to have greater waist to hip ratio for a given amount of abdominal fat suggesting that population specific criteria are needed for WHR.

Other studies have reported poor associations between measures of abdominal obesity and cardiovascular risk factors in groups of obese people (Haffner et al., 1986; Stern et al., 1986) suggesting that there is a „ceiling‟ level of centrally located adipose tissue (Després et al., 1990), above which the relationships with metabolic parameters are less apparent.

In general, men have a higher proportion of body fat stored centrally than women and the level of abdominal fat increases gradually with age. Women generally enter the middle years with a lower level of abdominal fat, but it begins to accumulate rapidly within this period so that by the seventh decade of life men and women have a distribution of body fat that is more equal. Some studies have suggested that abdominal 21

obesity does not really increase in women until after the menopause (Svendsen et al., 1995) but other studies indicate that the increase among women is more related to age (Wang et al., 1994).

1.2.3.3.4 Prevalence of Overweight and Obesity in Pacific Countries

Obesity has reached epidemic levels in developed nations in the Asia-Pacific region and is rapidly increasing in developing populations, especially Pacific Islands and certain Asian nations (WHO, 2000). All evidence suggests that the situation is likely to get worse. The increasing prevalence of overweight and obesity in Pacific people is enhanced by modernisation, acculturation and socioeconomic status (Zimmet, 1978; McGarvey, 1991; Tharman,1982).

High rates of obesity have been documented in many countries throughout the Pacific in both men and women. Although rates range from 2% in highland Papua New Guinea to nearly 80% in Nauru, in most communities the rate of obesity is well above 20%. The combined rate of overweight and obesity has been reported to be as high as 50% to 75% in many Pacific communities (Coyne et al., 2000).

The prevalence of obesity in the Pacific Island residents in New Zealand is 26% for males and 47.2% for females, more than double the prevalence of obesity in New Zealand Europeans and others (Russell et al.,1999).

There is also evidence of increasing weight in Pacific Islands. For example, in the Cook Islands, a study by Ulijaszek (Coyne et al., 2000) examined the trend in weight change among adult males aged 30 to 86 years. The mean BMI in 1996 of 142 Cook Island males was 30.3, a substantial increase since 1969 when the mean BMI was only 25.

1.2.3.3.5 Prevalence of Overweight and Obesity in Tonga

Despite the criteria for defining obesity being slightly different in each study, the prevalence of obesity is increasing in the kingdom of Tonga.

The Tongan Medical and Nutritional surveys (Koike et al. 1984) included 2 groups of Tongans aged 30 years and older - 108 from the remote island of Uiha, Ha‟apai in 1977 and 148 individuals from Kolofo‟ou (urban centre), Tongatapu in 1979. Males were significantly heavier than females. The mean weight for all female age groups exceeded 80 kg except for the age group above 70 years. Mean weight for males for all age groups exceeded 85kg for rural males and were close to 100kg for urban males.

Sawata et al. (1988) carried out a Cardiovascular Disease survey in 1983 which included 102 adults ranging in age from 21 to 91 years from Kolofo‟ou (Tongatapu) and „Uiha (Ha‟apai). The mean height and weight values for males and females were reported together as 173.9 + 6.3 cm and 87.4 + 15.2 kg respectively. These equate to a BMI of 28.9 kg/m2. The prevalence rates of obesity were not provided.

The 1986 Tongan National Nutrition Survey conducted by the Tonga Ministry of Health (Maclean, 1992) found that the most prevalent diet-related problem in Tonga was overweight and obesity. Overweight was defined as a BMI 25 - 30 kg/m2 for females and 27-31.9 kg/m2 for males, while obesity was defined as BMI  30 kg/m2 for females and BMI  32 kg/m2 for males. The study included 1605 women aged 15 to 49 years and 672 men aged 20 – 49 years. The mean BMI for females was 29.5 + 5.9 kg/m2 and for males was 27.6 + 3.8 kg/m2. There was a higher prevalence of obesity and overweight in females than in males. About 90% of females over 30 years of age had a BMI greater than 25kg/m2 and 39% of females and 10% of men were obese (BMI  32 kg/m2). Women tended to increase their weight with age in both urban and rural areas. A large percentage of younger women tended to be moderately overweight (BMI 25-30 kg/m2), with a national prevalence rate of 52.8% in women aged 15-20 years. Forty- eight per cent of men had BMI  27 (overweight) and 10% were considered obese (BMI  32 kg/m2). There was little difference between the mean BMI of rural and urban

Tongans.

The 1992 Non-Communicable Diseases and Nutrition survey (Foley et al., 1998) included 940 Tongans aged 14 to 70 years from Tongatapu (33%) and „Eua (67%) to represent the urban and rural areas of Tonga. Equal proportions of males (49.8%) and females (50.2%) were included in the sample and the mean age of the participants was 23

37 years. For females: overweight was defined as BMI 25 - 29 and Obese as BMI ≥ 30 and for males: overweight was defined as BMI 27-31.9kg/m2 and obesity BMI  32 kg/m2. Overall 42% of participants were obese and another 33% were overweight. The rates of overweight (BMI 25-29 kg/m2) increased with age to over 90% in the middle- age (30-39 years) among females. Rates of obesity were over 60% in middle-year age groups. Overweight and obesity were lower among males, but this may be due to the higher cut-off criteria used to define overweight and obesity in men - overweight was defined as BMI 27-31.9 kg/m2 and obesity as BMI  32 kg/m2. Using these criteria, rates of obesity for men were over 30% in the middle-age years and total overweight or obesity was more than 70%. There were higher proportion of obese males in the urban area (40%) than in the rural area (25%). There was a trend of increasing overweight and obesity with increasing age up to about 50 years when the level of obesity and overweight declined.

The prevalence of overweight and obesity has increased dramatically over the past years. Table 1.6 compares the prevalence of overweight and obesity in 1986 and 1992 survey conducted in Tonga, using the same criteria among females and among males.

Table 1.6: Comparison of prevalence of overweight and obesity in males and females according to BMI classification in the 1986 National Nutrition Survey and the 1992 Non-Communicable Diseases Survey in Tonga

% Overweight and/or Obese* Males Overweight Obese Overweight and Obese Age Group 1986 1992 1986 1992 1986 1992 10 - 19 - 21.7 - 16.7 - 38.4 20 - 29 34.8 39.3 3.8 19.3 38.6 58.6 30 - 39 34.6 42.0 14.5 32.0 49.1 74.0 40 - 49 45.4 34.7 15.8 43.1 61.2 77.8 50 - 59 - 31.1 - 40.5 - 71.6 60 + - 41.4 - 37.9 - 79.3 Total 37.6 35.7 10.0 29.8 47.6 65.5 Females % Overweight and/or Obese* Age Group Overweight Obese Overweight and Obese 10 - 19 52.8 15.4 8.9 30.7 61.7 46.1 20 - 29 43.4 32.0 32.0 38.1 75.4 70.1 30 - 39 27.2 30.6 62.8 60.5 90.0 91.1 40 - 49 25.3 23.0 65.7 67.0 91.0 90.0 50 - 59 - 31.8 - 59.1 - 90.9 60 + - 31.3 - 53.1 - 84.4 Total 38.8 29.3 39.7 54.8 77.9 84.1 * For females : overweight was defined as BMI 25 - 29 and Obese BMI ≥ 30 and for males: overweight was defined as BMI 27-31.9kg/m2 and obesity BMI  32 kg/m2 - No data available – age groups excluded in the study population

A cross-sectional comparative study of body weight between Tongans and Australians found significant differences. The sample included 543 participants (299 females and 244 males) from several villages in the Kingdom of Tonga and 393 participants (218 females, 175 males) from staff of Central Sydney Area Health Services, Australia. The Tongans were slightly older than the Australians for both females (40 vs 38 years) and males (40 vs 37 years). Tongans had a higher mean BMI compared with Australians for both men (30.3 vs 26.5) and women (32.6 vs 25.8) (Craig et al, 2001). Both Tongan women‟s and men‟s BMI increased with age.

Craig et al (1999) conducted a sub-study of the 1992 NCD survey which included 243 men and 299 women. The mean BMI in the sub-study by gender and age group was 25

compared with the 1986 National Nutrition Survey. The result reveals, as presented in Table 1.7, a higher BMI in 1992 for men in all age groups compared with the 1986 surveys. In women, the greatest differences were seen in the 30 – 39 years age group.

The body size preferences of different cultural groups may not coincide with the healthy weight ranges of BMI. Perception of body size is different in Pacific peoples compared with Caucasians. Large body size or being „pleasingly plump‟ is admired and may be perceived as being healthy, having wealth and status. A thin person can be perceived as sickly, suffering from illness (eg. having a malignancy) as well as having neglected self- care.

Table 1.7: Comparison of Body Size by BMI in Males and Females in the Nutrition Survey, 1986 and 1992 in Tonga

Females Males Age Groups 1986 1992 1986 1992

N 1471 299 681 242 20 – 29 26.2 ± 4.0 29.0 26.6 ± 2.9 28.1 30 – 39 28.3 ± 4.6 32.6 28.0 ± 4.3 31.7 40 – 49 32.3 ± 4.1 35.6 28.7 ± 4.4 32.2 50 – 59 - 34.2 - 31.0 60 + - 30.6 - 28.8 Total > 20 29.5 ± 5.9 32.5 27.6 ± 3.8 30.1 + no data available

It has been shown that Tongans preferred larger body sizes than Australians (Craig, 1999). A healthy Tongan female was considered to have a mean BMI of 26 kg/m2 compared with an Australian size of 21 kg/m2 while the mean preferred BMI of a healthy Tongan male was 28 kg/m2 compared with an Australian male BMI being 24 kg/m2. When these preferred body sizes were compared with weight categories „adjusted‟ to equivalent BMIs on the basis of % fat, the authors concluded that the Tongan body preferences for both males and females were reasonable and realistic. The Australian preferences also appeared consistent with the current recommended upper limit of 25 kg/m2, although the Australians preferred size was perhaps too low. 26

1.2.3.4 Thrifty Genotype

The “Thrifty Genotype” hypothesis was originally proposed to explain the unusually high incidence and prevalence rates of type 2 diabetes among Native American populations after World War 2 (Neel et al., 1962). Neel first proposed that a thrifty genotype conferred a survival advantage on populations subject to periods of nutritional hardship by favouring caloric conservation when food was abundant (Dyck, et al., 2001). Although humans have evolved thrifty mechanisms to defend energy stores during times of deprivation, they cannot easily prevent storage of energy when food is abundant (Ravussin et al., 1999).

The thrifty genotype was hypothesized as having a selection advantage when the earliest native Americans encountered particularly harsh feast or famine conditions as they moved into North America from Asia thousands of years ago. The environment was presumed to have favoured individuals with a quick insulin trigger, which resulted in greater fat storage when plasma glucose levels were highest during times of abundance. The fat then served as an energy reserve to be called up in more difficult times (The American Society for Nutrition Sciences, 2000).

According to Victoria and Barros (2001), certain populations worldwide, such as Polynesians, Australian Aborigines, and the Pima Indians in Arizona, have shown an exaggerated propensity to the development of type 2 diabetes. The problem emerged following extreme changes in lifestyle as a result of migration or changes in the natural environment of these populations. A probable explanation of this phenomenon is in traditional societies that have faced periods of feast and famine whereby a genotype has been selected that is associated with thrifty metabolic efficiency and survival capacity.

1.2.3.5 Hypertension

1.2.3.5.1 Brief Overview

Hypertension is a condition in which an individual has a higher blood pressure (BP) than is considered to be healthy. The definition of hypertension is continually evolving with recent definitions using lower levels of BP. When the survey which is the subject of this thesis was performed, hypertension in the general population was defined as a systolic blood pressure (SBP)  140 mmHg and/or diastolic blood pressure (DBP)  90 mmHg or of use antihypertensive medications. The definition of hypertension in people with type 2 diabetes was the same as for the general population (JNC-V1, 1997; WHO_ISH, 1999; NHF, 1999). More recently the definition has been lowered to SBP  130 mmHg and/or DBP  80 mmHg (JCN-VII, 2004).

There is a strong, graded and continuous relationship between systolic and diastolic blood pressure and risk of cardiovascular and cerebrovascular diseases. This includes stroke, coronary heart disease, heart failure and renal disease (Nutrition Taskforce, 1991; Abbott et al., 1987; Stamler et al., 1989; Stamler et al., 1993; Kannel et al., 1979)

Both systolic and diastolic blood pressure increase with BMI, and the obese are at higher risk of developing hypertension than lean individuals (Stamler R et al., 1978). Community-wide surveys in the USA (NHANES II) show that the prevalence of hypertension in overweight adults is 2.9-fold higher than that for non-overweight adults (Van Itallie, 1985). The risk of developing hypertension increases with the duration of obesity, especially in women and weight reduction leads to a fall in blood pressure (Pi- Sunyer, 1991). Hypertension also increases with age (Burton et al., 1985).

1.2.3.5.2 Hypertension in Tonga

The study by Finau and colleagues in 1973 (Finau et al.1986) showed that overall age- adjusted prevalence of hypertension (SBP ≥165, DBP ≥95 mmHg) was 8.4% with significantly more hypertension in Nuku'alofa (10.4%) than Foa (6.1%). The survey included 399 adults aged 20–69 years from the main urban centre of Nuku‟alofa and 28

392 from Foa (Ha‟apai) where the lifestyle was more traditional. The prevalence of hypertension by sex between the two areas was not significantly different. Systolic pressure increased significantly with age in all groups except rural men and was higher in urban dwellers in all age groups. There was no significant difference in diastolic pressure between the two groups.

The medical and nutritional surveys in 1977 and 1979 included 108 adults from the remote island of Uiha, Ha‟apai and 148 individuals from Kolofo‟ou, Nuku‟alofa (Koike et al. 1984). Six per cent of Tongans had diastolic pressures greater than 95 mmHg and 4% had systolic pressures greater than 160 mmHg. The results did not show differences between the rural/urban groups.

The survey of Sawata et al. (1988) of cardiovascular disease in 1983 included 102 adults ranging in age from 21 to 91 years. Mean blood pressure levels for both urban/rural groups and both genders combined were 129.5  16.0 mmHg systolic and 77.4  10.3 mmHg diastolic.

The non-communicable diseases and nutrition survey conducted in 1992 (Foley et al., 1998) included 940 participants from 14 to 70 years old from Tongatapu and „Eua. Blood pressure was measured in individuals 15 years and over. The prevalence rates based on systolic pressure  160 and diastolic pressure  95 indicated that 12 - 17% of Tongans had hypertension. There was a higher proportion of hypertension in the urban area. Self reported high blood pressure was noted by 2.8% of the participants, more females (4%) than males (1.7%). There was little difference between the urban and rural participants, 3.2% and 2.7% respectively. There was a trend of increasing hypertension with age, 4% of people over 35 years and 1.6% of people less than 35 years.

The Tonga Ministry of Health and the Prince of Wales Hospital national survey (Colagiuri et al., 2002) reported overall prevalence of hypertension of 37.3% in Tonga with age adjusted (≥ 15 years) prevalence of 31.9% in men and 30.8% in women. The

study involved 1024 Tongans age 15 years and older from Tongatapu, Vava‟u and Ha‟apai. Hypertension was defined as a systolic blood pressure ≥ 140 mmHg and/or diastolic pressure ≥ 90 mmHg or the use of anti-hypertensive medication.

In comparison with numerous small surveys from the 70s and 80s which used a higher cut off define of hypertension ( ≥ 160/≥ 95), it is difficult to know whether actual increases in hypertension have occurred over the years because more recent surveys have used lower cut-offs (≥ 140/≥ 90).

1.3 Food and Nutrient Intake

1.3.1 Brief Overview

Nutrients are substances in food which the human body needs to obtain in order to survive. Essential nutrients are those that the body cannot produce at all or in sufficient quantities to supply all our needs under normal circumstances. They are essential for human growth, maintenance and health (WHO/FAO/IAEA, 1996), and include carbohydrate (CHO), protein, fat, fibre, vitamins, minerals and trace elements.

The dietary pattern of a population or community reflects the usual habits of food selection and food preparation, and the contribution of nutrients and non-nutrient food factors, such that when one constituent of diet changes, the whole pattern of nutrients and food factors is modified (Gordon et al., 1984).

Knowledge of food consumption and nutrient intake trends is essential to health and nutrition policy makers, to food producers, and health officials to ensure the development of programs to meet the target population needs. Such information is also vital for formulating national nutrition recommendations, in developing health programs for combating chronic diseases and improving quality of life, and for designing interventional strategies to target sub-groups of the population (Hulshof et al., 1992).

Food-related behaviour is complex and determined by the interplay of many factors, including physiological factors, socio-demographic factors such as income, education

and occupation, behavioural and lifestyle factors such as physical activity, smoking, and knowledge and attitudes related to diet and health (Hulshof et al., 1992; Gonzalez et al., 1992).

Good nutrition and healthy eating habits are key factors in promoting good health and preventing non-communicable diseases.

1.3.1.1 Food and Culture

Food is central to all Pacific cultures. The gathering, preparation and shared eating of food are important social activities. In Tonga, the giving of food to guests, people in need (such as the ill) and people of status (the elderly, church ministers, chiefs and royal) is an outward expression of kinship, gratitude and generosity towards the receiver. Food is an integral part of all major occasions and is a form of social interaction (Parson, 1985). Food is a vehicle for communicating custom, a standard of wealth, a barometer of social status and a symbolic mediator in defining and manipulating kinship and social relationships (Moata‟ane et al., 1996, Kahn et al., 1985). It is an important way to show love and respect, to share, to express hospitality and to bring people together (Kinloch 1985; Vainikolo et al., 1993).

The traditional role and value of food in Pacific society is in stark contrast to the way food is viewed in the treatment of diabetes where it is primarily a source of nutrients. Pacific people tend to see food as something to enjoy rather than a source of nutrients needed to keep them healthy (Fitzgerald, 1980).

The cultural meaning of food for Pacific people must be respected. For example, while some traditional foods may lack nutritional value, their cultural value remains very powerful. The development of culturally appropriate food and nutrition programmes must include careful attention to these qualitative dimensions.

The cultural role of food has a major impact on Pacific people particularly with community activities such as feasting. Feasts are an important part of life of many Pacific people who live away from home. Feasts are a reminder of home and are an 31

important venue for family and social exchange (Pollock, 1989). Traditional food plays a central role in the Tongans who live in New Zealand, Australia and United States.

Food is important in all cultures and is a significant aspect of feasting and celebration (Fieldhouse, 1995; Pullock, 1989). It is important to appreciate however that there are differences in the intensity of the relationship with food in different cultures. For Samoans living in New Zealand, the value of food is in its ability to preserve traditions and help develop the community‟s unique identity (Bell et al., 1997).

Jamieson (1995) reported in her study with New Zealand women of low socio economic status that in spite of the difficulties, celebrations were vital for reinforcing the family and social networks. This is equally relevant for Pacific people.

1.3.1.2 Food Groups

In the Pacific region, foods are classified into three main groups (SPC, 2002). These are used to define a balanced diet and promote healthy eating. No single food or group of foods provides all the nutrients required. Each person should choose a range of foods from each of the main food groups to ensure nutritional needs are met.

The energy food group contains the carbohydrate foods, the body building food group includes the protein foods, both animal and plant origin, and the health and protective food group include fruits and vegetables, which are rich in vitamins, minerals and water. Traditional (local) foods are those naturally occurring in the environment. Types of food in each food group is presented on Table 1.8, and are further classified as local or imported food.

Table 1.8: Three Food Groups with food classified as local or imported food

Energy Food Local food: Root crops - taro, cassava, kumara/sweet potatoes, yam, coconuts and Starchy fruits - green banana, plaintain, breadfruit. Imported food: Flour and flour products, bread, dough pie dumpling cabin biscuits, porridge, cereals, rice, spaghetti, noodles, pizza Sugary products – jam, table sugar, cordial, soft drinks, lollies, ice-cream, doughnuts, cake, potato chips, fried potatoes

Body building Food Local food: Pork and piglet, beef, goats, chicken, ducks. Seafood - fish and jellyfish, sea cucumber Legumes and nuts – cashew, almond Imported food: Beef and salted beef, chicken, mutton flaps, turkey tails, spam, hot dogs, sausages, ham, eggs Tin food - tinned fish, corned beef Milk and milk products – condensed milk

Health and Protective Food Local vegetables : Green leafy vegetables – taro leaves, pele leaves (hibiscus), cabbages, lettuce, cucumber, tomatoes, carrots, pumpkin Imported vegetables : Frozen and tinned vegetables, broccoli, cauliflower Local fruits: pawpaw, watermelon, mangoes, guava, green coconuts, lime, lemon, sprouting nuts („uto) Imported fruits : apple, pear, oranges, grapes canned fruit

Generally, the foods included in a guide reflect the foods available in the food supply and the dietary practices and food consumption patterns of the population for whom they are intended. They are based on appropriate food choices, rather than nutrients, that need to be consumed to avoid deficiency.

1.3.1.3 Food and Nutrition Guidelines

A Food and Nutrition Guidelines for Tonga has been developed by the National Food and Nutrition Committee (1985). It‟s primary focus is on specific changes in food consumption and dietary practices to reduce the risk of chronic diseases by promoting the consumption of local food. These selection guides were based on Recommended Daily Allowances (RDA) use in the United Kingdom and findings from past nutrition

surveys conducted since the 1950‟s. The food and nutrition guidelines are quantitative in recommending food or food groups to „eat more‟ or „eat less‟. With the high prevalence of obesity and increasing NCD in the Kingdom of Tonga, it is timely to review the feasibility of the National Food and Nutrition Guidelines in improving the nutritional status of the Tongan people. Hence, this is one of the aims of undertaking this national nutrition survey to specifically examine detailed nutrient intake which will assist in formulating practical health and nutrition programmes to improve nutrition status in the Kingdom of Tonga.

Food and Nutrition Guidelines in Tonga aim to promote eating a variety of food from the three food groups, especially the local food, to have lots of fruits and vegetables, to drink plenty of fluid, promoting water as the best, and to limit the amount of fats, salt and sugar. The non-food aspects of the guidelines recommend increased physical activity, to achieve and maintain a healthy weight, avoid smoking, and if drinking alcohol then have it in moderation.

The Food and Nutrition Guidelines also stress that too much of any one food is unhealthy, and to eat the right amount from the three food groups. This should help individuals to make choices about what to eat to keep them healthy. The guidelines are relevant to all adult Tongans.

Unfortunately, serve size or portion is not used in Tonga. Current education is trying to address food size, however most starchy foods vary in size, even when they are cooked and served. For example, one person can say that they eat 2 pieces of taro, and the size can range from 100–250g (1/2 cup – 1 cup).

1.3.1.4 Recommended Dietary Intake

Many countries have developed a set of nutrient recommendations to meet the nutritional needs of a healthy person. They are also known as recommended daily allowances, recommended daily amounts, reference nutrients, dietary reference values and safe intake. In Australia, the current term is recommended dietary intake (RDI) and it is defined as 34

Recommended dietary intakes (RDI) are the levels of intakes of essential nutrients, considered in the judgment of the National Health and Medical Research Council, on the basis of available scientific knowledge to be adequate to meet the known nutritional needs of practically healthy persons. The RDIs are derived from estimates of requirements for each age/sex category and incorporate generous factors to accommodate variations in absorption and metabolism. They therefore apply to groups needs. RDIs exceed the actual nutrient requirements of practically all healthy persons and are not synonymous with requirements (NHMRC, 1991)

The purpose of nutrient recommendations is to define a standard diet for groups of the population with different age, sex, size, and physiological status (Truswell et al., 1983). RDI is the basis for various programs such as evaluating dietary intakes, nutrition education, food programs and so forth. However, the overriding nutritional goal is to increase the proportion of the population who consume a diet consistent with the Australian Dietary guidelines and, as such, they tend to focus on foods and macronutrients that are not included in the RDIs (such as fats and sugar).

Populations comprise lean and overweight individuals, and energy control may override other dietary requirements for certain individuals. Environmental influences alter the food supply and food selection. Since there is no single “ideal” dietary pattern, dietary recommendations must whenever possible, respect the traditions, cultural implications, palatability and convenience of currently existing dietary habits.

1.3.2 Nutrient Intake and Non-communicable Diseases

Poor food and nutrient intake are key factors that contribute to the increasing rate of NCD in the Pacific region. Poor nutrition and inadequate physical activity as a result of changing lifestyles have contributed to this phenomenon (Bathgate, 1994; Tukuitonga et al., 1990; Muimuiheata, 1995, NZ Ministry of Health, 1997; Crocombe et a., 2003; Bloom, 1986).

Modernisation, urbanisation and association with western culture are strongly associated with changes in Pacific people‟s lifestyle and diet (Thaman, 1982; Coyne, 1984). When the European pattern of living and eating became more common in many Pacific countries, including Tonga, the major causes of death shifted from communicable diseases to non-communicable diseases such as diabetes and cardiovascular disease (Prior, 1971; Zimmet et al., 1981). It is hypothesised that these lifestyle changes interacted with genetic factors, which in the past favoured fat storage so people could survive food shortages but which today have become a disadvantage because they lead to overweight (Swinburn, 1995).

The association between diet and chronic diseases such as hypertension, type 2 diabetes and cardiovascular disease has been recognised since the 1970 when Keys and others linked dietary factors with hypertension and elevated blood cholesterol levels (Keys et al., 1992). Since then, a multitude of studies have confirmed these associations, particularly with dietary fat (US National Research Council, 1989; WHO, 1990; Kromhout et al., 1995). Among Pacific islands people, it appears that modern dietary and lifestyle factors unmask a genetic predisposition for type 2 diabetes and possibly cardiovascular disease (SPC, 1984; Hodge et al., 1995).

Dietary patterns that emphasise fat sources from plant oils, nuts and seeds, and fish, reduce risk factors for CVD when compared with patterns rich in animal fats, hardened plant fats and oils, commercial products containing these fats and deep fried foods.

Recently, dietary trials have demonstrated that dietary interventions targeting dietary fats alone, without also improving fruit, vegetable and dietary fibre intakes, do not achieve optimal risk reduction. Optimal risk reduction and maximal nutrient intakes are achieved when a large proportion of a high carbohydrate intake is high in fibre and mainly from fruit, vegetables, legumes and whole grains (Bucher et al., 1999; Truswell, 1998; Dyslipidaemia Advisory Group of the New Zealand National Heart Foundation, 1996; AHA Taskforce on Risk Reduction, 1998; NZ Dietetic Association, 2000).

The traditional dietary pattern of many Pacific Island countries is one that supports a low blood pressure. It is low in salt, rich in potassium, magnesium and other trace 36

minerals, high in fibre, and most likely rich in omega-3 fatty acids derived from fish oils. The urbanized diet is generally the opposite - high in salt, almost devoid of potassium and low in fibre and omega-3 fatty acids (Beaglehole et al., 1975; Vainikolo et al., 1993; Swinburn et al., 1997; Salmond et al., 1989; Hodge et al., 1994, Hodge et al., 1997; Coyne et al., 2000).

1.3.2.1 Nutrients, Diabetes and Cardiovascular Disease Risk Factors

The most frequently measured risk factor outcome from dietary intervention trials for reducing cardiovascular risk is total blood cholesterol, and the most frequently studied dietary change, reduced total and/or saturated fatty acids. When other risk factors are included in the assessment of dietary benefit, other dietary factors become prominent supporting the results of observational studies (Bucher et al., 1999). There is now a consensus that dietary fat as a risk factor for chronic disease should not be considered in isolation from a whole diet approach that constitutes the full set of dietary recommendations (Truswell, 1998).

Epidemiological studies demonstrate an association between reduced risk of CVD, hyperlipidaemia and hypertension and dietary patterns rich in plant foods compared with patterns that include considerable quantities of animal fats and/or hardened plant fats and oils (Keys et al., 1986; Verschuren et al., 1995; Menotti et al., 1999; Keys, 1970; Kromhout and Menotti, 1995; Thorogood et al., 1994; Key et al., 1996; Kato et al., 1973; Campbell et al., 1999; Ge, 1995; Gen et al.,, 1995 ).

The most fundamental component of the diabetes treatment plan for all people with type 2 diabetes is medical nutrition therapy (ADA, 2000; Nutrition Taskforce, 1991), specifically aiming to achieve and maintain as near-normal blood glucose levels as possible. In an ideal situation, euglycaemia is achieved without the aid of oral hypoglycaemic agents or exogenous insulin. Thus, the management of type 2 diabetes hinges on nonpharmacological measures, such as diabetes education, diet, exercise and weight control (Dagogo-Jack et al., 1997).

The ideal diet for people with diabetes needs to take into account not only the effects of foods on glycaemic control but also the longer term influences on plasma lipids and insulin which may in turn influence macrovascular and microvascular complications (Riccardi et al., 1987).

1.3.2.1.1 Current Nutrition Recommendations for Diabetes and Cardiovascular Risk Factors

Adequate diet for people with type 2 diabetes should supply all essential nutrients and therefore does not differ from the nutritional requirements of healthy people. However, due to the specific and increased cardiovascular risk for those with diabetes, their dietary advice includes nutritional guidelines formulated for subjects at high risk of cardiovascular disease (Toeller, 1993)

Weight reduction is the key to good glycaemic control in the majority of people with type 2 diabetes who are overweight and present with insulin resistance. Thus, nutritional modification to slow the rate of carbohydrate absorption is a useful measure for avoiding rapid increase in blood glucose concentrations following food intake (Toeller, 1993).

1.3.2.1.2 Total Energy Intake

Energy intake should be equivalent to the requirements needed to maintain or achieve a suitable body weight. Clinical observation has indicated that a close relationship exists between food intake and the development and management of diabetes and cardiovascular disease risk factors (Toeller, 1993).

If the total energy intake is greater than the energy expended over a period of time, it is highly likely that obesity will develop in an otherwise healthy individual (Bray, 1996). Recent studies have suggested that nutrients may have different effects on satiety and the conversion of excess energy intake to body fat stores, and thus may influence the onset of obesity. For example, it is thought that carbohydrate has a greater satiety effect

but will be less efficiently converted to body fat stores when compared to dietary fat (Anderson, 1996; Lissner et al., 1995). Physical activity will also favourably influence energy balance (Bray, 1996).

1.3.2.1.3 Dietary Fats

Different types of dietary fats have been shown to affect risk factors and markers of CVD (Grundy, 1996). Low intakes of saturated fats, and relatively higher intakes of poly- and mono-unsaturated fats have been shown to have a beneficial effect (NHMRC 1992; Weber & Leaf 1991; Daviglus et al.,1997; Dolocek 1991; Lichestein 1996).

People with type 2 diabetes, who are at high risk for developing cardiovascular disease, are recommended to restrict total fat intake and to modify the composition of fat, which is often high in saturated fatty acids (SFA) (Toeller, 1993).

Various studies indicate that SFA leads to a rise in blood cholesterol (Stone, 1990; Keys et al., 1986; Hu et al., 1997). Not all SFA affect blood cholesterol levels equally. Dairy fats result in the most atherogenic fatty acid profile and appear to have greater thrombogenicity than those found in meat (Nordoy et al., 1990; Renaud et al., 1989). Animal products per se have not been found to consistently raise blood pressure levels. Prescott and colleagues (1988) found a lack of a role of meat in the differences in blood pressure seen between vegetarians and non-vegetarians.

Coconut is a staple food in many Polynesian Islands (Prior et al., 1981). Coconut differs from nuts in that it is high in SFA with 91% of the fat saturated. Studies provide contradictory findings with regard to the effect of coconut oil on blood lipids (NZ Heart Foundation, 1999). The diet and cholesterol levels of Tokelau and Pukapuka Islands, indicated that coconuts provide over half (63%) of the energy consumed by Tokelauans and 35% of the energy consumed by Pukapukans. The Tokelauans had significantly higher total cholesterol levels compared with Pukapukans (Prior et al., 1981). Two New Zealand studies compared the effect of coconut with other fats on blood lipids. Cox and

colleagues (1995) and (1998) concluded that butter has a greater hypercholesterolaemic effect than coconut oil.

Fats may also play an important role with respect to insulin resistance and therefore may be important in type 2 diabetes (Vessby, 1995).

High intakes of polyunsaturated fat (PUFA) are associated with reduced CVD risk (Brown, 1990). Omega-6 and Omega-3 PUFAs appear to have different mechanisms of action in reducing cardiovascular risk. Diets high in marine-source of omega-3 PUFA do not lower total cholesterol, but lower triglyceride (TG) levels, an effect which is more marked in those with hypertriglyceridaemia (Daviglus et al., 1997; Webber & Leaf 1991). This has been associated with reduced risk of stroke among Greenland Eskimos (Dyerberg et al., 1975) and also has been shown to be effective in reducing blood pressure in overweight hypertensive people, especially when combined with a weigh reduction programme (Endres et al., 1995; Bao et al., 1998; Stone, 1996). This is not seen with plant-source omega-3 PUFAs (de Deckere et al., 1998; Simpoulis, 1999)

Monounsaturated fat (MUFA) appears to lower both total cholesterol and LDL- cholesterol, with little change in HDL-cholesterol levels (Grundy, 1986). The reduction in cholesterol is seen even when the total fat intake is unchanged (Wardlaw et al., 1990). MUFAs may be an important component of the diet for the management of diabetes (WHO/FAO/IAEA 1996).

1.3.2.1.4 Carbohydrates

Carbohydrates are the major source of energy in the diet. Considerable evidence has been accumulating with respect to the role of different types of carbohydrate (fibre, complex carbohydrate and resistant starch) and the management of blood glucose in diabetes (Salmeron et al., 1997a; Salmeron et al., 1997b). In excess, refined carbohydrates may influence obesity, diabetes, and other risk factors for CVD.

The current recommendation for adult‟s diet is for carbohydrates to provide 50–55% of total energy (NZ Nutrition Taskforce, 1991). The Dietitians Association of Australia (DAA) recommends that for people with type 2 diabetes, complex carbohydrate should contribute more than 50% of total energy and refined sugar intake no more than 5% of total energy intake (NHMRC, 1998). A diet which is high in complex carbohydrate and low in fat leads to a natural caloric restriction due to consumption of a large proportion of low-calorie foods.

Moderate intake of carbohydrate in combination with a low SFA intake has been shown to reduce total cholesterol and LDL-choleterol and to improve the LDL-to HDL- cholesterol ratio in free-living subjects with normal or elevated blood lipids (Jenkins et al., 1997; Abbot et al., 1989; Turley et al., 1998; Lewis et al., 1981; Mustad et al., 1999; Jones et al., 1987; Joshipura et al., 1999).

1.3.2.1.5 Dietary Fibre

Dietary fibre may modify risk factors for the development of CVD such as plasma lipids (Truswell, 1995). Several epidemiological studies suggest high intakes of fibre may protect against development of heart disease (Rimm e al., 1996; Pietinen et al., 1996).

Consumption of soluble fibre has been associated with both improving glucose and lipid control in people with diabetes. It is therefore recommended that foods rich in soluble fibre are prominent in the diabetes diet (Toeller, 1993).

Dietary fibre may help in the prevention and management of CVD by lowering blood cholesterol and promotion of weight loss. An increased fibre intake is usually seen in vegetarians when compared with the general population (Rouse et al., 1981; Rouse, et al. 1984). When Kelsay and colleagues (1978) altered fibre intake alone no reduction in blood pressure levels occurred in normotensive individuals but there was a slight decrease in diastolic blood pressure in mildly hypertensive subjects. Other studies have shown that a high fibre diet leads to blood pressure reduction (Anderson, 1983; Wright et al., 1979).

1.3.2.1.6 Glycaemic Index

Until the end of 1970‟s, it was believed that carbohydrate in foods were either available or unavailable for humans, absorbed in the small intestine or not absorbed (Jenkins et al., 1979). Available carbohydrates were assumed to all be digested and absorbed at the same rate and to have the same effect on postprandial blood glucose (Truswell, 1992).

Jenkins and colleagues (1981), devised the Glycaemic Index (GI) as a method to standardize the way of testing the glycaemic impact of different carbohydrate containing foods. The GI score of a food is determined by calculating the incremental area of the postprandial glucose of that food and expressing it as a percentage of the area under the postprandial glucose curve for a reference food (glucose of white bread), with the carbohydrate content being equivalent in both foods (Brand et al., 1991; Brand- Miller et al., 2003).

Thus the glycaemic index reflects the effect of a food‟s carbohydrate content on blood glucose levels and can therefore be used to rank foods according to their glycaemic effect. Results of studies in healthy, young adults of normal weight agree well with those in middle aged or elderly, overweight patients with diabetes (Jenkins et al., 1984).

Many past studies have demonstrated the beneficial effects of low GI diets, not only in people with diabetes, but also for sports performance and weight loss (Brand et al., 1996; Jarvi et al., 1999; Salmerron et al., 1997b)

Wolever et al., (1992) found that reducing the overall glycaemic impact of the diet, without changing the nutrient composition or dietary fibre content, resulted in significant improvements in blood glucose and lipid control despite only a modest weight reduction. Jenkins et al. (1992) found significant reductions in fasting blood glucose, HbA1c and urinary c-peptide-to-creatinine ratio in subjects with type 2 diabetes on a low GI diet.

1.3.2.1.7 Proteins

Protein dietary requirements is approximately 15% of energy. Although it is not known whether a higher protein intake (>20%) will have a detrimental effect on renal function of people with diabetes without early signs of nephropathy, it is recommended that protein intake should not exceed daily requirements (Toeller, 1993).

Franz et al. (2002) recommends an intake of protein between 15 – 20% of total energy and two or more servings of fish per week to provide sufficient omega 3 polyunsaturated fatty acids. They also point out that ingestion of protein stimulates insulin secretion though it is not as potent as glucose (carbohydrate). However Franz does not recommend a high protein intake (and low in carbohydrate) as the long-term effects are unknown. They acknowledged that such diets may produce short-term weight loss and improved glycaemia, but it has not been established that the weight loss can be maintained in the long term plus there is the concern of the long term effect on the LDL cholesterol.

Moderate hyperglycaemia in obese patients may contribute to an increased turnover of protein in type 2 diabetes as there is an increase in whole-body nitrogen flux and a higher rate of protein synthesis and breakdown (Gougeon, 1994)

1.3.2.1.8 Vitamins and Minerals

Sodium has been implicated in contributing to high blood pressure (Nutrition Taskforce, 1991). However, it has been shown that increased sodium intake does not increase blood pressure in all individuals and sodium restriction does not lower blood pressure in all hypertensive people (Korhonen et al., 1999).

Ophir and colleagues (1983) determined that vegetarians had higher potassium intake which may contribute to the lower blood pressure levels seen in individuals adopting

this dietary regimen. However, evidence to date about the role of potassium is inconclusive.

Low dietary calcium has been linked to the development of hypertension (National Heart Foundation, 1999; Curhan et al., 1993). However, an association between lower calcium intake and increased BP is not conclusive (Nutrition Taskforce, 1991).

A very high fruit and vegetable intake (at least 400g per day) and a low SFA eating plan can lower the SBP and DBP in normtensive and mildly hypertensive people (Appel et al., 1997). This may also improve total cholesterol, LDL-chol. HDL-chol. TGs and fasting blood glucose (Law et al., 1998; Rimm et al., 1996a; Key et al., 1996; Gaziano et al., 1995).

It has recently been suggested that decrease intracellular magnesium content may contribute to the impaired insulin response and activity seen in people with type 2 diabetes and that long-term supplement could contribute to an improvement in islet ß- cell response and insulin activity (Toeller, 1993). However, this remains unproven.

1.3.2.2 Food and Nutrient Intake in the Pacific Countries.

The trends in food consumption are relatively similar between different Pacific Islands, particularly in terms of changing food consumption patterns. Dietary change has been strongly associated with modernisation in many Pacific communities, encompassing modernisation within Pacific nations themselves (Galanis et al, 1999; Koike et al. 1984; Lako, 2001) and upon migration to more developed countries such as New Zealand (Prior, 1981b; Vainikolo et al., 1993; Finau et al., 1987; Bell et al., 1996).

Modernisation in Pacific Islands has resulted in economic and social benefits which have been accompanied by a rapid change in lifestyle behaviour. When once subsistence agriculture was the norm, modernisation has moved the focus onto cash cropping, thus providing increased monetary returns and greater purchasing power. This transition has brought about dramatic changes in diet and physical activity levels.

The most notable change in diet due to modernisation has been a shift from a larger proportion of energy from starchy carbohydrate to an increased proportion of energy from fats, animal proteins and refined or simple carbohydrates (Bathgate et al, 1994; Drewnowski, 1997; Gill, 2000).

Diet varies widely in the Pacific depending on environmental limitations. For example, in the highlands of Papua New Guinea, traditional diets derive 95% of energy from carbohydrate and 2% from fat. In atolls such as Kiribati where diets are based on coconut and fish, energy contribution from fat can be as high as 36% (Hodge et al, 1996). Modernisation has brought about a gradual reliance on cereals and sugars, less consumption of traditional roots and tubers and increasing consumption of fats and oils (FAO, 1996).

Migration has had a predictable effect on dietary patterns. Tongans living in Dunedin (Vainikolo et al., 1993) reported marked changes in food consumption patterns following migration to New Zealand. There was an increased consumption of meat, dairy products, fats and oils and consequently higher intakes of energy, total fat, protein, cholesterol and calcium in Dunedin compared with Tonga.

Studies describing the migration of Tokelauans to New Zealand 20 to 30 years ago have shown that major dietary changes have occurred (Helmrich et al., 1991). The changes occurred quite quickly after migration and included shifts in the primary sources of nutrients and energy in the diet from coconut, traditional cereals and fish to meat, more refined cereals, dairy products and sugar. While food sources changed dramatically, the percentage of energy from fat, protein and carbohydrate did not change to the same extent. A similar study of Samoans migrating to Hawaii and other American States, found that dietary changes with migration included increases in energy intake, saturated fat and dietary cholesterol, refined sugar and sodium, and a decrease in dietary fibre (Hanna et al., 1986).

The nutrient intake of Europeans, Maori and Pacific Island men and women in New Zealand was compared in a study by Metcalf and colleagues (1998). They found overall that Pacific Islanders consumed more total energy, sucrose, protein, total fat, saturated 45

fat, monounsaturated fat and cholesterol per day compared with European New Zealanders. Pacific Island men however consumed less fibre and calcium than Europeans, whilst Pacific Island women consumed more carbohydrate, starch and polyunsaturated fat then European women. The ethnic differences in nutrient intakes observed in this study were due to larger portion sizes and increased frequency of intake of most foods by Pacific Islanders.

Other studies have shown a low consumption of fruits and vegetables among Pacific Islanders (Bell et al, 1997). However, a study by Gonelevu and colleagues (1997) found no significant difference in fruit and vegetable consumption between Polynesian and European women aged 18 to 27 years.

A dietary study of Samoans living in Samoa and those living in American Samoa showed that American Samoans had a significantly higher carbohydrate (47% vs 44%) and protein (18% vs 13%) contribution to energy than the Samoans living in Samoa. However, the energy contribution from total fat (36% vs 46%) and saturated fat (16% vs 30%) was significantly lower (Galanis et al, 1999). Another study conducted in three Samoan church communities in Auckland found a higher proportion of energy intake from soft drinks, takeaways and snacks in subjects aged less than 40 years, compared with the older group. In addition, intake of fruits and vegetables was very low (Bell et al, 1997).

In summary, energy supply sources have switched from starchy root crops to fat, cereal and sugar. The major nutritional changes from a traditional diet are an increase in total fat, especially from meat, a decrease in fibre, and an enormous increase in simple carbohydrates, and a probable increase in salt. In terms of food types, there has been a decrease in vegetables, fruit and fish with an increase in bread, rice, biscuits, sugar and sugar-based soft drinks.

1.3.2.3 Food and Nutrient Intake in Tongan

Langley (1952) with the South Pacific Health Services carried out a quantitative dietary survey in Tonga, using 24 hour dietary recall. Participants were 22 adults (11 male, 11 46

female) and 27 children between 5 and 15 years of age, and 3 infants from Kolovai (rural village in Tongatapu). The study reported an average daily caloric intake for adults of 3290 calories and 69g protein. Protein was mainly from plant sources such as pumpkin, sweet potatoes, hibiscus (pele leaves) and taro. Meat was eaten only once or twice a week. Cassava was the most important root crop eaten followed by yam and then sweet potatoes. Bread was eaten commonly.

Adachi of the Japanese Gerontolgy Research Project (1976) carried out nutrition study in 1976 and 1977 (Englberger, 1983) as part of a medico-nutritional study to determine the physiological state of Tongans in „Uiha (Ha‟apai). Dietary intake was studied by food record (observation and food weighing) on 2 days (Thursday and Sunday) in 22 adult participants. Findings indicated that both calorie and protein intake were generally very high. Daily energy intake in 4 out of 16 females was > 3000 calories and in 4 out of 6 males was > 4500 calories. One female and one male had daily caloric intakes of 6489 and 5889 respectively. Protein was also high with 60% being of animal origin. Nine females and all of male (6) participants had over 45g protein and 6 out of the 24 participants had over 100g protein per day.

The Finau et al. (1987) study in 1973 used the 24-hour recall method and reported that urban people in Nuku‟alofa ate more imported foods such as mutton, chicken, beef, tinned fish and more meals with flour products than rural people in Foa. Rural people consumed more fresh fish and shellfish than did urban people. This study revealed that Nuku‟alofa people were consuming western-type foods whereas the Foa people were eating traditional foods. Similar findings were reported in the 1986 National Nutrition Survey in Tonga (Maclean et al., 1987). Consumption of imported foods was highest among urban adults while rural participants tended to consume more local produce of starchy roots or fruit crops, coconut cream at most meals, and fish on a daily basis.

A national survey carried out in 1986 randomly selected women aged 15–49 years, men aged 20–48 years and children up to 4 years old. The 24 hour recall method was employed. This study found a low incidence of anaemia among women except one area where the incidence of mild anaemia was high. The survey also indicated that the differences in dietary patterns between urban and rural areas were attributable to 47

availability of foods. Rural adults tended to consume more local produce. Consumption of imported foods was highest among urban adults (Maclean et al., 1992).The rural- urban differences were probably due to a combination of factors such as greater availability of foods, an inconsistent supply of local foods or the lower cost and convenience of obtaining and cooking of staples. For the Ha‟apai islands, the diet consisted predominantly of local starch roots or fruit crops, coconut cream at most meals, and fish which usually eaten only once a day.

A study among Tongan and Tokelauan school children in Auckland, New Zealand (Bell, 1995) found diets with larger caloric intake but lower in micronutrient density compared with diets of non-Pacific Island children. The major sources of energy in the diet were meat, bakery products, fast foods such as meat pies, potato chips, takeaways and dairy products. It was concluded that their diets predisposed to obesity if maintained into adulthood, and put them at risk of type 2 diabetes and cardiovascular disease.

A review of 13 food and nutrition surveys carried out in Tonga (Englberger, 1983) showed an increasing difference in urban and rural dietary intake with all surveys suggesting that the diet in all outer islands and in both rural and urban areas increasingly lacked healthy and protective foods such as fruits and vegetables. Younger people ate more imported foods than older people. In Tongatapu, the consumption of sugar and sugary snack foods was particularly high. Overall meals were not well balanced and morning meals in both urban and rural areas tended to be the least balanced.

Of particular concern has been the increasing consumption of imported high fat meats eg mutton flaps and turkey tails. The 1992 Nutrition Survey indicated that mutton flaps was the most frequently consumed meat (Foyer et al., 1998). Thirty one percent of the study population consumed mutton on a daily basis and 27% consumed it three or more times a week. A higher proportion of urban than rural people ate chicken regularly.

1.4 Lifestyle Risk Factors

1.4.1 Exercise and Physical Activity

1.4.1.1 Brief Overview

Physical activity is an important lifestyle factor that can help to maintain energy balance, reduce risk of obesity, and improve general well-being.

Prospective studies strongly support the view that sedentary lifestyle is associated with increased risk of CVD (Sandvik et al., 1993). Adopting a lifestyle that includes moderate physical activity in middle age appears to have a beneficial effect on that risk with reduction in total cholesterol and LDL cholesterol and concomitant increase in HDL cholesterol (Berlin et al., 1990; Tran et al., 1985). One study has shown that moderate physical exercise decreases mortality (Erikssen et al., 1998).

Exercise is a subset of physical activity. It is planned, structured and repetitive bodily movement performed to improve or maintain one or more components of physical activity. Exercise is often performed to achieve objectives such as improved fitness, performance and health, and can provide a means of social interaction. Exercise is a foreign term to the Tongan population, as their physical activity involves a call of duty and work to provide for the family.

Physical activity includes a combination of planned activity and exercise, lifestyle activity, and spontaneous physical activity.

Moderate physical activity is defined as activities with energy expenditure of 3 to 6 METs. A MET is defined as a multiple of the resting metabolic rate (McArdle et al., 1991). People who perform activities of this intensity for 30 minutes per day will meet the recommendations for cardiovascular benefit. Vigorous physical activity is defined as activities with energy expenditures of greater than 7 METs (Althuis et al., 2002).

1.4.1.2 Physical Activity, Diabetes and Cardiovascular Disease

Regular physical activity is associated with reduced risk of CVD morbidity and mortality. Sedentary occupations compared with active occupations have almost doubled the risk of CVD (Berlin et al., 1990). This observation is consistent over a range of intensities and frequencies with the more intense and frequent activity conferring greater protection (Manson et al., 1999; Joliffe et al., 2001). The protective effect of physical activity is greatest in individuals at higher risk of CVD (Joliffe et al., 2001). Limited evidence from small randomized controlled trials show that the improvements in cardiorespiratory fitness, lipid profiles and blood pressure from physical activity comprising several short sessions per day are as effective as those comprising longer continuous sessions (Hardman, 1996).

1.4.1.3 Physical Activity in Tonga

Most people in Tonga perform regular physical activity which varies with gender and age.

Household chores are a woman‟s duty in Tonga. These included food preparation, sweeping the house, making beds, washing dishes/clothes, sweeping/picking up rubbish and fallen leaves around the home. Women tend to do low intensity activity but for longer periods.

Working in the plantation or the bush is considered as a man‟s job in Tonga. This is the most common and undoubtedly the most intense of the physical activities. The combination of dry land and the sweltering heat adds to the intensity of slashing, digging, planting and the harvesting of food crops. Most Tongan families engage in agriculture for their own produce which is how they obtain their main staple foods to feed the family.

Walking exercise is a scientific approach to physical activity that may not be respected in the Tongan culture. In fact, walking has to have a purpose, such as walking to the shops, to church, or to visit relatives and friends otherwise it is seems abnormal to walk 50

as an exercise. Before transportation was available in Tonga, the people would walk from village to village to visit relative or to tend their plantation.

In Tonga, not everyday of the week is the same in terms of physical activity. Saturday tends to be the day when most activity takes place, whether at home doing housework, or working in the bush. A typical Saturday is considered a bush day, where people not only tend their plantation but also makes preparations for the week ahead by harvesting crops, collecting firewood etc. Saturday is also the day to collect and prepare materials for Sunday‟s traditional food preparation.

Sunday is literally considered the day of prayer and rest. It is a day when food is traditionally prepared in the morning, followed by church attendances, and then by a heavy lunch of traditional dishes, and siesta afterwards. In this respect, very little physical activity takes place on a Sunday. Changing times have brought about a few changes in terms of food preparation and lifestyle. For example, all families prepare food in the traditional oven but some used an electric oven and other time and labour- saving appliances. All in all, only very little light activity takes place on a Sunday.

1.4.2 Smoking

1.4.2.1 Brief Overview

Tobacco use has been identified as a major preventable cause of premature death and illness (Conrad et al., 1992; Peto et al., 2001). The WHO attributes 4.9 million deaths a year to tobacco use, a figure expected to rise to more than 10 million deaths a year by 2030 (Peto et al., 2001). The WHO reports that daily smoking rates throughout the world increase substantially across age groups (WHO, 2000).

1.4.2.2 Smoking, Diabetes and Cardiovascular Diseases

The evidence linking cigarette smoking with cardiovascular disease is incontrovertible (Doll et al., 1994; Phillips et al., 1996). Cigarette smoking is one of the leading causes of mortality in the world and it accounts for one out of every five deaths in the United 51

States (Haire-Joshu et al., 1999; ADA, 2000). The risks of smoking increase with the amount of tobacco smoked daily and with the duration of smoking. Stopping smoking significantly reduces CVD risk, although it may be several years before the risk is reversed (Kottke et al., 1994).

Disproportionate health impacts from smoking are common in indigenous people in developed countries. The prevalence of conventional cardiovascular risk factors such as smoking can explain, in part, the difference between life spans of indigenous and non- indigenous peoples. Among Australian Aboriginal and Torres Strait Islander populations CVD is the single most common cause of premature death and disability and smoking is one of the principal health behaviours that leads to their life span being nearly 20 years less than other Australians (Lindoff, 2002). This compares to a five to six year differences in NZ between Maori and Non-maori, a seven-year gap in Canada between indigenous and non-indigenous peoples and 3.5 years in the United States between indigenous North Americans and others (Lindoff, 2002).

1.4.2.3 Smoking in Tonga and Pacific Countries

Finau et al. (1973) investigated lifestyle risk factors such as smoking tobacco and drinking alcohol and kava and found that the prevalence of smoking was higher in urban than rural areas.

More males than females smoke in Tonga. This probably reflects traditional and cultural constraints that have prevented women from smoking. In 1991, a survey conducted in Tonga reported that 60.4% of males and 9.8% of females aged 20-24 were current smokers (Woodward et al., 1994).

The 1992 National Nutrition Survey in Tonga (Foley et al., 1998) indicated that smoking is a habit which is initiated before 12 years of age in about 6% of males. The majority of male smokers began in their teens, with age 15 to 16 years being the most common age for starting to smoke. Females tended to begin smoking later than males, with the majority beginning after the age of 20. Rural smokers reported smoking a greater number of cigarettes per day than the urban smokers. 52

A study about prevalence of smoking among Pacific communities in Auckland (Connor et al., 2005) reported that 41% of Tongan respondents reported ever having smoked tobacco. Thirty one percent had used tobacco in the past and 26% had smoked tobacco over the past month. Thirty nine percent of Tongan men had smoked in the previous year compared with 24% of Tongan women. Tongan women in the 30-65 year old age group were less likely to smoke than their male counterparts. Tongan women aged 30- 65 years were less likely to smoke than women of the same age from the total Pacific sample.

In New Zealand the trend is that there are more men then women smokers. Smoking data were collected in the 1981 Census and 42% of Pacific men and 24% of Pacific women smoked (NZ Department of Statistics, 1981). The study by Scragg et al. (1991) found that in the multi-cultural workforce 41% of the Pacific Islands men and 21% of Pacific Islands women smoked.

In addition, in Western Samoa Collins et al., (1996) found that 50% of males and 19% of females smoked.

The Tokelau Island Migrant study found that smoking rates increased among Tokelauns living in New Zealand between 1972-1974, and 1982, particularly for young people (Wessen et al., 1992).

1.4.2.4 Smoking and Religion

One of the fundamental beliefs of the Latter Day Saints (LDS) church and Seventh Day Adventist (SDA) church, is abstinence from alcohol and tobacco. Any form of tobacco is believed to be a slow killing addictive poison, which affects the body physically and mentally. Use of this „drug‟ is considered by the church as breaking the sixth commandment, „Thou shalt not kill‟, found in Exodus 20:13 (The Bible King James Version, 1989).

1.4.3 Alcohol

1.4.3.1 Brief Overview

Alcohol use currently represents one of the most significant risks to health globally. The WHO estimates that about 76.3 million people have been diagnosed with alcohol use disorders. In most parts of the world, morbidity and mortality rates relating to alcohol consumption are considerable (WHO, 2004a).

Worldwide, alcohol causes 1.8 million deaths each year, and 4% of disability adjusted life years (DALYs), with the majority of DALYs occurring in Europe, the Western Pacific and the Americans (WHO, 2005). Overall, there are causal relationships between alcohol consumption and more than 60 types of disease and injury (WHO, 2004a) and major alcohol-related health conditions contributing to illness, disability and death (Babor et al., 2003).

While alcohol consumption has been falling in many developed countries, there is concern about increased drinking and intoxication among young people, including many under the legal minimum age of purchase (WHO, 2002).

Recommendations for those who choose to drink alcohol should limit regular intake to 2 drinks daily for women, 3 drinks for men, and mostly avoid binge drinking (Mann et al., 1999). Consumption of alcohol should be discouraged in situations of pregnancy, liver cirrhosis, uncontrolled hypertension, congestive heart failure, haemorrhagic stroke, high risk of breast cancer, and pancreatitis (Mann et al., 1999). Consumption of alcohol should be restricted further with hypertriglyceridaemia, hypertension, elevated uric acid, abdominal adiposity, obesity, and weight reduction.

1.4.3.2 Alcohol, Diabetes and Cardiovascular Disease

Epidemiological observations suggest that women under 55 years of age and men under 45 years of age derive no cardiovascular benefits from the consumption of alcohol. Protective effects associated with drinking alcohol are mostly confined to coronary 54

heart disease in people consuming 10-30 grams of alcohol daily (New Zealand National Heart Foundation, 1999). For individuals with obesity, abdominal adiposity or hypertriglyceridaemia, even recommended intake limits may be contraindicated.

Twenty or thirty grams of alcohol daily has been associated with hypertension in women (Ascherio et al., 1996) and men (Ascherio et al., 1992) respectively. A J-shaped curve defines upper limits of safe intakes in terms of mortality. Low risk drinking guidelines have been defined as two or fewer alcoholic drinks per day with consumption not exceeding 14 standard drinks per week in men and nine standard drinks in women (Campbell et al., 1995). Randomised controlled trials demonstrate an association between alcohol intake and blood pressure above these levels in normotensive individuals. An association below this level is less clear (Campbell et al., 1999). Interventions have measured the effects of reducing alcohol on blood pressure since ethical considerations preclude studies increasing alcohol consumption.

Moderate alcohol intake has been associated with reduced cardiovascular events in a number of population surveys (Pearson, 1996). This association is found with wine but also with other alcoholic beverages (Rimm et al., 1996b, Gaziano et al; 1999). Unlike a number of other potentially beneficial dietary substances, the addition of alcohol as a cardioprotective substance cannot be recommended. Alcohol can be addictive, and its intake can be associated with serious adverse consequences, including hypertension, liver damage, risk of breast cancer, physical abuse, and vehicular accidents. For this reason, and based on available epidemiological data, the National Health and Medical Research Council recommends that if alcoholic beverages are consumed, they should be limited to the equivalent of 2 drinks (30 g ethanol) per day for men and 1 drink per day for women (Pearson, 1996). Individuals who choose to consume alcohol should also be aware that it has a higher caloric density than protein and carbohydrate and is a source of additional “empty” calories.

Many individuals have to limit their total intake of all fats and oils, alcohol and low fibre, and refined carbohydrate foods, in order to avoid concentration of energy intakes and subsequent weight gain and increase of waist circumference.

1.4.3.3 Alcohol in Tonga and Pacific countries

Alcohol was unknown to the Tongans until introduced by early explorers, sailors and traders. Before long, the Wesleyan missionaries permit system enabled only wealthy people to buy alcohol leaving others to make home brew („hopi‟) and sometimes even methylated spirits. These habits are still symbols of westernization and considered to show familiarity and seasoned acquaintance with the new prestigious life style. Access to alcohol in Tonga was traditionally restricted to the privileged and some speculate that this is why „binge drinking‟ – making the most of alcohol when it‟s around – has prevailed. Alcohol consumption in Tonga has been alluded to by anthropologist (Lemert, 1967; Urbanowicz, 1975).

In stark contrast to the alcohol bans at home, when Tongan migrants arrived in New Zealand they found that alcohol was freely available to everyone – no matter what their social status. While it is generally understood among Pacific cultures that abstinence is the preferred option, alcohol soon became a feature at most social events, family gatherings, weddings, birthdays, community dances and sporting events.

The prevalence of alcohol consumption in Tonga stands at 21.3% of the population. Trend data is unknown, but anecdotal evidence indicates a steep rise in consumption since 1989, when legislative controls on alcohol consumption were removed. Unpublished reports suggest that tobacco and alcohol were responsible for 10.4% of the non-communicable disease hospital admissions and 19.6% of all hospital expenditure in 2002 (Puloka, 2004).

In Tonga, alcohol, like tobacco is much more likely to be consumed by males than females and urban drinkers consumed alcohol more often than their rural counterparts and younger people drank more regularly than the older population (Foley et al., 1998; Finau et al., 1982).

The Nutrition and Health Survey (1992) included nine hundred and fifty participants age 14–70 years selected from Tongatapu (33%) and „Eua (67%). Respondents were asked a range of questions to assess their knowledge, attitudes and practices in relation 56

to alcohol consumption. More than 90% of females but less than 50% of male respondents said they never drank alcohol. Urban drinkers drank more often than their rural counterparts and younger people drank more regularly than those older than 34 years. The majority of drinkers began consuming alcohol in their teen years, with about one-tenth of both male and female drinkers beginning before the age of 15 years. Alcohol was usually consumed in a context to either help socializing or relaxing. One quarter of the drinkers linked drinking with social, work or health problems.

There is limited information available on alcohol use in the Cook Islands. A survey conducted in 1993 found that 91.3% of males and 85% of females start drinking by 16 years of age. Annual consumption of alcohol is approximately 4.8 litres per person. High consumption is linked to ready availability of alcohol (Teokotai, 2004).

Alcohol use is an accepted part of Fijian culture. Alcohol is readily available and binge drinking is common. Alcohol is freely advertised and aggressively marketed. Twenty six percent of males and 9% of females are current drinkers. Of the drinkers, forty seven percent of males and one-third of females started drinking before 10 years of age (Chang, 2004).

Limited information exists on alcohol use and consumption in Niue. Binge drinking and weekly drinking are very common (Pulu, 2004). In addition, no consumption figures are available for Papua New Guinea but levels of alcohol consumption and binge drinking are high ( Dagam, 2004) . Teenage drinking is increasing and boys as young as 12 years old drink alcohol. A recent survey found that 26% of 13 to 18 year olds drink alcohol regularly. It is mainly males who drink and mainly in towns, although rates of females drinking are increasing. Binge drinking occurs mainly during the weekend, but also during the week and at parties. Some members of the younger population drink methylated spirits (Dagam, 2004).

In Samoa, the level of consumption is similar to levels in Vanuatu and Fiji, higher than levels in Papua New Guinea, and lower than levels in the Cook Islands. Sixty percent of young people, mostly males, in the Solomon Islands drink alcohol. . 57

1.4.3.3 Alcohol and Culture

Traditionally there have been strong religious and social restrictions on the use of alcohol but less so with kava and tobacco (Lemert, 1967; Shulgin, 1973). Initially the missionaries prohibited alcohol consumption among converts and later incorporated this prohibition into the Tongan law (Rutherford, 1971). The Tongans took their religious and government leaders at face value and most obeyed.

The ALAC‟s Alcohol and Pacific Island Research Projects in New Zealand (1997) indicated that both men and women spoke of the cultural belief that Tongan women should not drink. Women who do not drink are seen as “molumalu” (ladylike, dignified). Both women and men felt that men saw women who drank as being “real easy”, that is, sexually available.

CHAPTER 2

2. OBJECTIVES

2.1 Brief Overview

The National Diabetes and Cardiovascular Diseases Risk Factor, Nutrition and Physical Activity Survey was a component of the Diabetes and Cardiovascular Diseases Prevention and Control Project in the Kingdom of Tonga. This is a joint effort of the Ministry of Health in Tonga and the Diabetes Centre, Prince of Wales Hospital (POWH), Sydney, Australia to prevent and control the rapid increase and burden of Non-communicable Diseases. The project was funded through an AusAID grant.

2.2 Objectives and Aims

There were two objectives in the National Diabetes and Cardiovascular Diseases Risk Factor, Nutrition and Physical Activity Survey:  to determine the prevalence of diabetes, impaired glucose metabolism and the risk factors for diabetes and cardiovascular diseases among the Tongan population  to describe the food and nutrient intake and physical activity in this population in order to establish baseline data for future surveys and to use current information for planning health services to combat the increasing prevalence of diabetes and other NCDs.

The specific aims of this thesis were to  Determine the national pattern of macro-nutrient intake in Tonga  Identify associations between macro-nutrient intake with overweight, obesity and glucose tolerance

2.3 My role in the study

I was primarily responsible for  Designing the nutrition and lifestyle part of the survey  Data Collection – personally involved, trained and supervising of the other staff involved in the nutrition data collection  Entering the nutrition data into the database  Designed the analysis of the data  Interpreting the results of the nutrition data and its relationship to diabetes, overweight, obesity and physical activity  Writing up the findings as presented in this thesis.

During the field work, I worked closely with the project team from the POWH and Tonga Ministry of Health and with local communities at each island to ensure the smooth day-to-day running of the project and to maintain good relationships between the local community and the diabetes project team. During the analysis phase of the project I worked closely with the POWH team.

CHAPTER 3

3. STUDY DESIGN AND METHODS

3.1 Brief Overview

The overall sampling procedure was designed in collaboration with the Department of Statistics, Government of Tonga. This was undertaken by drawing a random sample based on various characteristics derived from the 1996 Census data.

The target sample for the survey included Tongan nationals 15 years of age and older. The 1996 census documented a total of 59,526 people (60.9% of the total population) in this age group.

A multi-stage cluster sampling design was used to select a representative sample of the target study population. The required sample was chosen through a selection of a set of census blocks, households within these selected census blocks and one respondent within the household.

3.2 Timing of Survey

The survey was conducted in two parts, Tongatapu in 1998 and Vava‟u and Ha‟apai in 2000. The Tongatapu survey was conducted over a six-week period during September and October, 1998 at the Tonga National Cultural Centre, opposite the main hospital, Vaiola Hospital.

The Vava‟u and Ha‟apai survey was conducted over a three-week period during March and April, 2000 at each hospital site, situated on the main islands.

3.3 Survey Team

The staff involved in the survey included health professionals from the Ministry of Health, Tonga and the Prince of Wales Hospital, Sydney.

The survey team from the Vaiola Hospital Diabetes Centre included 3 Staff Nurses, 2 Dietitians, 1 Physician and other team members were 1 Laboratory Technician and 2 Health Educators from Vaiola Hospital.

The survey team from Tongatapu travelled to Vava‟u and Ha‟apai, and worked with the local survey co-ordinators at each hospital.

The town/village officer was the representative for each selected census block and was the local contact person. He/she assisted with promoting the survey and ensuring that the selected participants were contacted and available to attend the survey site.

3.4 Subject Selection

The Department of Statistics in Tonga randomly selected census blocks in Tongatapu, and a random selection of villages in Vava‟u and Ha‟apai. A list of all households under the name of the head of the household was constructed. The household consisted of people who usually eat together and share the work of preparing the food and/or the cost or work of providing it.

Tongatapu was divided into 273 census blocks which were stratified into urban and rural areas. A three stage sampling design was used to select the survey participants. The first stage was the random identification of 34 census blocks from urban areas and 68 census blocks from rural areas which reflected the ratio of urban to rural areas in Tongatapu. Secondly, every 4th house was systematically selected within each census block. Thirdly, one male or female 15 years and over was selected alternatively from each household based on birth date closest to 1st January. This method of selection was designed to facilitate matching the age and sex distribution of the survey and Tongan population.

In Vava‟u and Ha‟apai, all villages and island groups were classified as rural areas. The first stage was the random selection of villages and islands. Secondly, every 4th house was systematically selected within each village or island. Thirdly, one male or female 15 years and over was randomly selected alternately from each household based on birth date closest to 1st of January.

3.4.1 Exclusion Criteria

A number of standard exclusions from the study population were made. These were people who were already diagnosed with diabetes, pregnant women, non-Tongans, intellectually handicapped or patients with a psychiatric illness and those who were critically ill.

3.4.2 Household Contact

The staff at the Diabetes Centre (Tongatapu) and Public Health Nurses (Vava‟u and Ha‟apai) visited the selected household prior to the survey to assess suitability and willingness to participate in the survey. All consenting eligible participants were given an appointment to come to the survey site between 0800 and 1000 hours on a particular day.

In Tongatapu, two public transport vans of the Ministry of Health were organised to pick up participants who needed transportation to the survey site. The village town officer organised participants to be picked up at a central venue, usually the town hall or a church hall.

Initially 832 subjects were selected (rural:621 and urban:211) in Tongatapu for participation in the study. Among those eligible subjects, 45 refused to participate, 61 consented but failed to attend and 50 were unavailable at the time of survey. A total of 66 individuals were excluded from participation - 16 with self-reported diabetes and the others because they were either ill or because they were not Tongans. Two subjects were not included in the analysis because of missing information. Overall there was a total of 608 participants giving a response rate of 79%.

In Vava‟u and Ha‟apai, those from the outer islands were brought to the survey site by boats organized by the local co-ordinator, the Public Health Nurse.

In Vava‟u and Ha‟apai 527 people were invited to participate, of whom 25 were ineligible (10 with known type 2 diabetes), 20 refused to participate, 22 agreed but did not attend, and 44 were unavailable. In total, 416 people participated (202 in Vava‟u and 214 in Ha‟apai), giving a response rate of 83%.

3.5 Promotion of the Survey

In Tongatapu, during the month of July-August, 1998 community meetings were held at the selected census blocks to create public awareness of the national survey and its purpose. This was organized by staff from the Public Health section of the Ministry of Health.

The survey was subsequently advertised on local television, radio, local newspaper and also through the survey team personally contacting the local communities.

In Vava‟u and Ha‟apai, the local survey co-ordinators (Public Health Nurse and/or Health Officer) covered the survey purpose and details on their daily home visiting activities. Therefore there was no need for any community meetings. In addition, the Vava‟u and Ha‟apai participants had learnt about the first part of the survey that was carried out in Tongatapu.

3.6 Survey Procedure

3.6.1 Staff Training

One day before the survey, health survey training was given to the survey team in such tasks as registering participants, interviewing techniques, completing the food frequency questionnaires and assisting people with the details of the survey and procedure. These activities were complemented by the survey team from the Diabetes Centre (Vaiola

Hospital) who were responsible for taking physical measurements, assisting with registration and making a final check of everyone‟s questionnaires.

Each survey team member was allocated to a specific work-station designated for each procedure as detail in section 3.6.2

The ethics approval was obtained in Australia from the University of New South Wales Human Research Ethics Committee.

3.6.2 Data Collection

At the time of the survey Tonga did not have a formal ethics approval process. However the study was approved by the Tongan Ministry of Health. Participants were not required to complete a written consent form. Since verbal communication is still very much the accepted mode of communication for the Tongan population, verbal consent is accepted as an agreement to participate in the survey.

Participants were given an appointment to come to the survey site between 0800 and 1000h. The assessments required all participants to fast overnight and collect an early morning urine sample. All specimens collected during the survey were sent to the Prince of Wales Hospital in Sydney, Australia for analysis.

Daily attendance rates varied between 20 to over 40 people. If the survey participants failed to attend, the diabetes team made a second visit to the household to arrange another appointment.

All participants were seated in the waiting area on arrival. Each survey morning, the survey started with an opening prayer, lead by a participant or by a member of the survey team.

A bowl of water with soap and a clean towel were available where each participant was asked to wash their hands before proceeding to the registration desk.

The survey was performed in the following order:

3.6.2.1 Registration

Each participant was given a registration number and their urine sample was collected. Trained interviewers administered a pre-designed questionnaire that collected general information (Appendix 1). The questionnaire was available in English, but the interview was conducted in the Tongan language. It included questions on demographic, personal medical history, current health status, family history of first degree relatives with diabetes, and lifestyle related risk factors notably smoking status, alcohol consumption, exercise and physical activity and use of traditional medicine. The specific components were:

3.6.2.1.1 Demographics and Medical Characteristics

Age, gender, type of occupation, religion or church attended and residential address were recorded.

Participants were asked whether they have a first degree relative with diabetes, about their personal medical history, with a particular focus on cardiovascular disease.

3.6.2.1.2 Smoking Status and Alcohol Consumption

People were asked if they currently smoked cigarettes, and if so, how many. Those who did not smoke were asked if they had smoked regularly in the past. Similarly, participants were asked if they currently drank alcohol. Those who responded yes, were also asked how many times a week they drank and how many drinks per occasion. One drink was defined as: - One can of beer, half a big bottle of beer, one stubby bottle or one-third of a jug - One glass of wine or sherry - One nip of spirits

Those who were not current drinkers were asked if they drank regularly in the past.

3.6.2.1.3 Traditional Medicine

Participants were asked whether they were taking any type of traditional medicine or non-medical treatment.

3.6.2.2 Anthropometric Measurements

Measurement of height, weight, waist and hip circumferences were taken. The participant was asked to remove heavy jewellery and empty their pockets before weight measurements were made. Outer garments such as coats or jumpers were also removed although Tongans rarely wear such garments. The measurements were made by the interviewer and recorded by the assistant. The measurements were made in the following order:

3.6.2.2.1 Height Measurement

Height was measured in the standing position with a Microtoise which consists of an L- shaped device (the head-bar) to which was attached a spring-loaded coiled tape measure. The free end of the tape was secured with a nail to the wall directly above the head-bar. The head-bar is then raised above the height of the participant who was asked to stand directly below the point of attachment.

The participants were asked to remove their shoes and to stand with their feet flat on the floor, heels together, and heels, buttocks and shoulder blades in contact with the wall. The participant‟s back was as straight as possible, their arms hanging loosely by their sides and was then positioned by the interviewer such that the line of vision was parallel to the floor. The participant was asked to breath in deeply and stretch to their fullest height, without altering their head position. The head-bar was then lowered by the interviewer until it touched the crown of the head and compressed the hair. The height measurement was taken at maximum inspiration, with the interviewer‟s eyes level with the head-bar to avoid parallax errors.

The measurement was made to the nearest millimetre and if the reading fell between two values, the lower reading was recorded. In cases where large amounts of adipose

tissue prevent the heels, buttocks and shoulders from simultaneously touching the wall, participants were asked to stand erect.

3.6.2.2.2 Weight Measurement

The weight measurements were performed in the fasting state without shoes and in light clothing. Seca digital medical platform scales (Model 770) were placed on the hard flat wooden floor and checked for zero-balance before each measurement. The participants were asked to stand unassisted in the centre of the scales with their feet together, arms hanging loosely by their side, standing relaxed and head facing forward. Two measurements were made to the nearest 0.1 kg. The participant was asked to step away from the scales between each measurement. If the two measurements differed by more than 0.5 kg, a third measurement was made.

3.6.2.2.3 Body Mass Index (BMI)

BMI was calculated as weight (kg) over height (m) squared.

3.6.2.2.4 Circumference Measurement

Waist and hip circumference measurements were taken over one layer of light clothing using a long diameter tape and recorded to the nearest 0.1 cm. All measurements were taken with the tape in a horizontal position at the end of a normal expiration, with the tape pulled firmly but not causing indentation.

Waist circumference was taken at the horizontal level between the xiphisternum and the pubic symphysis. Hip circumference was taken at the horizontal level at the maximum circumference around the buttocks when viewed from the side. The waist-to-hip ratio (WHR) was then calculated.

WHO criteria were used to classify WHR and waist circumference. High WHR was defined as ≥ 0.95 for men and ≥ 0.80 for women (Lean et al., 1995). Normal waist circumference was defined as < 94 cm for men and <80 cm for women. Men with waist circumference  94 cm and < 102 cm and women with waist circumference ≥ 80 cm

and < 88 cm were defined as „increased risk‟. Men with waist circumference  102 cm and women with waist circumference  88 cm were defined as „substantially increased risk‟ (WHO, 1997; American Diabetes Association, 1998).

3.6.2.2.5 Bioelectical Impedance (BIA)

The bioelectrical impedance (BIA) is a portable, fast and easy, non-invasive reliable and suitable method for estimating body composition of an individual (Chumlea et al., 1994, Guo et al., 1996).

Resistance and reactance were measured at 50 kHz using a SEAC bioimpedance analyser (Model BIM4, Impedimed, Capalaba, Australia) with a tetrapolar arrangement of self-adhesive electrodes.

The measurement was carried out fasting and participants were asked to empty their bladder. Measurements were carried out with participants lying supine with arms near their bodies (but not touching) and legs parted. The skin of the right hand and foot were swabbed with alcohol before the electrodes was placed.

Electrodes were placed on the right hand and dorsum of the right foot. The midline of the electrode was placed on the crease made when the wrist or ankle is flexed. Two electrodes were on the dorsal surfaces of the hand and foot proximal to the metacarpo- phalangeal and metatarso-phalangeal joints, respectively. In addition, two sensing electrodes were placed at the right anterior ankle between the tibial and fibular malleioli and the right posterior wrist between the styloid process of the radius and ulna.

Each measurement was repeated at least twice to ensure readings were within a precision of 2 ohms. The mean values of resistance, impedance and reactance were used in the analysis, and the percentage of body fat (% Body Fat) is presented as part of the Anthropometric Characteristics.

3.6.2.3 Clinical and Metabolic Measurement

3.6.2.3.1 Blood Pressure

The OMRON 706C smart-inflate blood pressure monitor was used with either a standard or large cuff. No stethoscope is required with this machine. The OMRON monitor has automatic inflation and records pulse, systolic and diastolic pressures.

The procedure was explained to all participants before the blood pressure measurements started. The participant was asked whether any blood pressure medication was taken and this was recorded. Participants were seated at a table, with their right arm resting on the table so that their inner elbow was level with their heart. Blood pressure was measured to the nearest 2mmHg while in the sitting position in the right arm after 10 minutes rest. Blood pressure was measured over the bare skin where possible. The large cuff was used if the arm circumference was greater than 35cm. Where the interviewer was unsure, the large cuff was used initially and changed to the small cuff if necessary.

Systolic blood pressure (SBP) was recorded at the level of appearance of sound and diastolic blood pressure (DBP) at the level of sound disappearance (phase V). Hypertension was defined as SBP ≥140mmHg and/or DBP ≥90 mmHg or the use of anti-hypertensive medication (American Diabetes Association, 1998).

3.6.2.3.2 Blood Glucose and HbA1c

Fasting venous blood was collected in all participants for measurement of plasma glucose and lipids including total cholesterol, HDL cholesterol, and triglycerides. In addition each participant had a fasting capillary whole blood glucose level measured by finger prick using a portable Hemocue meter (HemoCue AB, Angelholm, Sweden), and

HbA1c was measured using the DCA 2000 analyzer (Bayer, Elkhart, IN) (normal range 4-6%).

3.6.2.3.3 Oral Glucose Tolerance Test (OGTT)

A standard OGTT was performed with a fasting venous blood collection for measurement of plasma glucose, ingestion of 75g glucose monohydrate dissolved in 250 ml water, and collection of another blood sample 2 hour later.

All participants with a fasting capillary whole blood glucose >5.0 mmol/l and <11.1 mmol/l underwent an oral glucose tolerance test (OGTT). Subjects with a fasting blood glucose 5.0 mmol/l and an HbA1c >6.0% also had an OGTT. In addition, every fifth subject with fasting blood glucose 5.0 mmol/l and a normal HbA1c level also had an OGTT. A total of 472 individuals had an OGTT based on these criteria.

Participants with a fasting blood glucose 11.1 mmol/l and an elevated HbA1c level were diagnosed as having diabetes.

3.6.2.3.4 Blood Samples

Three vacutainers of blood were collected from each participant. Each vacutainer was labeled and colour coded at the time of collection.

All venous blood samples were promptly centrifuged, plasma separated and stored at – 20 C, and air transported to the Prince of Wales Hospital in Sydney for analysis of glucose, lipids and creatinine.

3.6.2.4 Nutrition and Lifestyle Survey

3.6.2.4.1 Food Frequency Questionnaires (FFQ)

Food-frequency questionnaire is a questionnaire in which the respondent is presented with a list of foods and is required to say how often each is eaten in broad terms such as x times per day/per week/per month. Foods chosen are usually for the specific purposes of a study and may not assess total diet (Cade et al., 2001)

Questionnaires may either be developed from basic principles or adapted from existing questionnaires (Gibson, 1990). There weren‟t any FFQ specifically developed for the Tongan population and as time and finances were limited, the use of pre-existing questionnaire was particularly appealing. FFQ used in the New Zealand National Nutrition Survey (Quigley et al., 1997) was modified for this survey. Modification of the existing FFQ was important as the questionnaire was developed for a different population, and also need to include commonly eaten foods and recipe dishes used in the Tongan population. The list of foods included 213 food items and focuses on specific groups of foods, particularly foods that are available in Tonga such as staple food, fruits, vegetables and some local meat as listed in Table 1.8. The FFQ was designed to obtain semi-quantitative, descriptive information about the usual daily intake of food and nutrients (Anderson, 1986).

The questionnaire was administered by trained interviewers and the questionnaire was available in English, although the session was conducted in Tongan. The interviewers adhered to a set questioning routine to minimise their influence on the responses. Each interview to administer the FFQ lasted between 20–30 minutes.

The questionnaire consists of two components - a list of foods and a set of frequency-of- use response categories, which describes how often foods or beverages are consumed and also some indication of the amount eaten. During the interview, the interviewer used food models (households serving size) for a better estimation of the real portion consumed by the subject. Participants were questioned about frequency of intake for different foods during the last 3 months and were asked to report the frequency of these intakes in terms of day, week or month (Appendix II). A few foods were consumed more than once a day and this tends to lead to gross overestimates for some people. The sub-questions allowed a better definition of the food items consumed. For example, following the questions “How often do you eat taro?” subjects were asked about how many pieces of taro he or she would eat in one day. If subject eats taro 3 days a week, and have 5 pieces per day, this means that the total amount of taro is 15 pieces per week. Portion and serving size were important, and participants were asked to describe their serving size small, medium or large (where the medium portion was specified). The food models were used for participants to select their own portion size.

Seasonally consumed food items could be problematic when reporting on frequency as they may be consumed very frequent when in season and then not at all out of season. As this is very important, sub-questions were asks about consumption of seasonal items when „in season‟. For foods that are eaten infrequently but make a significant contributions to nutrient intake (eg sea food), it was included on the sub-questions, say less than once a month. Cross-check question was also used to correct for over reporting of certain food groups, especially for fruits, vegetables and staple food as they were e listed singly in the food list. The data was then adjusted at analysis to reflect length of time in the season.

A detailed description of each food and beverage item was ascertained through a series of questions and prompts specific to each item. Questions for each item included: amount eaten, the cooking method, type of fats used in preparation and any recipe where appropriate. An open question at the end of the FFQ allowed subjects to report any other frequency eaten foods not listed in the FFQ and provide details about usual recipes used in order to quantify better intake of individual food items. If the participant did not know the recipe of a mixed item, probe questions about ingredients likely to influence the fat content of the food (for example type of fat, whether coconut milk was used) were asked

All questionnaires were checked by the author with another dietitian (member of the survey team) for completeness. Participants would be asked to complete any missing part before leave the survey area. The author was also available during the interview session providing support to the interviewer if required.

3.6.2.4.2 Physical Activity

The interviewer asks the participants about their occupational and their daily activities. Activity levels were assessed in terms of whether or not participants, in a normal week, were involved in vigorous and/or moderate activity and the frequency of that activity per week. Vigorous was defined as activity that caused a person to sweat or breathe hard, such as working out at the gym, working in the plantation or playing touch rugby. Moderate activity included lighter activities such as walking, playing volleyball or

cycling. People were considered to be sedentary if they said they did no moderate or vigorous activity

The intensity of the activity was determined according to the scale shown in the questionnaire form (Appendix III).

3.7 Data Analysis

3.7.1 Biochemical Analysis

A fasting venous blood sample was collected for measurement of plasma glucose and lipids including total cholesterol, HDL cholesterol and triglycerides and for measurement of serum creatinine. Blood sample assays were performed using a Beckman LX20 analyser. Glucose was determined using the hexokinase method, total cholesterol using cholesterol esterase, oxidase and peroxidase to produce quinoneimine products, HDL cholesterol after solubilising with detergent, triglycerides after hydrolysis to glycerol by lipase, and creatinine after reacting with alkaline pictrate. LDL cholesterol was calculated as follows:

total cholesterol – triglycerides – HDL cholesterol 2.2 provided that triglycerides were <4.0 mmol/L.

Abnormal level were defined as total cholesterol ≥5.5 mmol/L, HDL cholesterol <1.0 mmol/L, triglycerides >1.7 mmol/L and creatinine >0.11 mmol/L. Urine was analysed for albuminuria, expressed as albumin:creatinine ratio. Urine albumin was measured by the immunoturbidimetry method. Microalbuminuria was defined as 2.5 - 30.0 mg/mmol for men and 3.5 - 30.0 mg/mmol for women

Diabetes, impaired fasting glucose (IFG), and impaired glucose tolerance (IGT) were defined according to the WHO diagnostic criteria (WHO, 1999) as in Table 3.1

Table 3.1: Values for diagnosis of diabetes mellitus and other categories of hyperglycaemia*

Glucose concentration (mmol/l (mg/dl)) Whole blood Plasma Venous Capillary Venous Capillary Diabetes Mellitus: Fasting 6.1 (110) 6.1 (110) 7.0 (126) 7.0 (126) Or 2-h post glucose load 10.0 (180) 11.1 (200) 11.1 (200) 12.2 (220) or both Impaired Glucose Tolerance (IGT): Fasting concentration (if measured) 6.1 (110) 6.1 (110) 7.0 (126) 7.0 (126) And 2-h post glucose load 6.7 (120) 7.8 (140) 7.8 (140) 8.9 (160) And And And And 10.0 (180) 11.1 (200) 11.1 (200) 12.2 (220) Impaired Fasting Glucose (IFG): Fasting 5.6 (100) 5.6 (100) 6.1 (110) 6.1 (110) And And And And 6.1 (110) 6.1 (110) 7.0 (126) 7.0 (126) 2-h (if measured) 6.7 (120) 7.8 (140) 7.8 (140) 8.9 (160)

*The values for diagnostic criteria given in the table have been taken from the report of a WHO consultation

3.7.2 Nutrient Analysis

Evaluation of nutrient intakes derived from the FFQ was performed using the Australia FoodWorks® Professional edition (version 3.01.472, 2003, Xyris Software, Brisbane). The primary source of food was the Australia and New Zealand Food Composition Database, which contains more than 2000 foods, including a variety of Pacific Island food. This is compiled and regularly updated by Food Works Ltd. The software allows the updating of foods, if they are not currently in the database. Therefore where a direct match with information in the database was not available for a food which was used often, additional nutrient composition data were sought from relevant overseas databases (Pacific, USDA and British). In cases where a food or beverages was not available, it was substituted with closest food type, of the same food group. For the purpose this part of the study, intakes of selected nutrients susceptible to affect NCD

risk profile were analysed: energy, protein, carbohydrates (CHO), lipids, saturated fatty acid (SFA), monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), total dietary fibres. Student t test were performed to verify variation in nutrients intakes. All analysis were performed with the SPPS statistical package version 12.0 (SPSS 12.0) for windows for group analysis. Nutrients were calculated from FFQ based on the frequency of consumption. Total number of intake can be calculated from the sum of products of the frequency weight and nutrient content of the portion of food. Means and standard deviation were calculated.

A data base of portion sizes was also compiled (Appendix IV). The specific portion sizes used were households‟ servings or average amount (Dignan et al., 2004). For example . 1 cup 250 g . 1 bowl 220 g . 1 glass 200 mls . 1 tsp 5 mls/g . 1 tbs 10 mls/g . 1 whole banana 140 g . 1 serve breadfruit 166 g . 1 cup cassava 227 g . 1 serve kumara 213 g . 1 serve yam 209 g . 1 sausage 79g . 1 steak 172 g . 1 bowl mutton flaps 220 g . 1 serve beef 200 g . 1 serve of fish 150 g . 1 slice bread 40g

When a food, beverage and cooking method could not be completely described by the respondent (for example the person had milk but did not know the type) it was matched to the type most commonly used in Tonga. This was based on the author‟s work experienced and knowledge of local food available in Tonga. For example, Homogenized UHT milk (full cream) is the most readily available milk in Tonga.

The nutrient content of mixed dishes was estimated from recipes that include foods for which the nutrient composition is known. Participants who consumed a mixed dish, such as chop chey, may or may not have known the recipe. When the exact recipe was not known, information regarding content was sought from the participant, for example, whether meat was added, in order to identify which recipe provided the best nutrient match. Where nutrient composition information only for the dish as a whole was available, it was grouped accordingly. Some recipes (ingredients and amounts) were obtained from the Pacific Islands Food Composition Tables (Dignan et al., 2004) (Appendix V)

3.7.3 Physical Activity Analysis

Activity levels were assessed in terms of occupation and whether the participants, in a normal week were involved in vigorous and/or moderate activity and the frequency of that activity per week.

Occupation was divided into 4 groups: – professional based on the level of physical activity involved in the job – labourer based on the level of physical activity involved in the job – domestic, which included house work and those who worked in the plantation or – students which included high school and tertiary education students

The interviewer asked the individual about the average hours of participation in occupational and extracurricular activities over a typical 24-hr period.

The intensity of the activity was also assessed according to categories shown below:

Exertion level Hot Breathlessness Sweating 0 no no no 1 mildly mildly no 2 yes yes some 3 yes yes a lot

Calculations

The physical activity level were calculated by using activity Code for the Bouchard Three Day Physical Activity Record (Bouchard et al., 1983)

Activities are quantified on a 1-to-9 scale of energy cost. A physical activity index composite score was calculated by summing the number of hours spent in each exertion intensity level and multiplying by a respective weight factor derived from the estimated oxygen consumption requirement for each intensity level. All participants were allocated an 8 hr of sleep, and the different intensity level weights are shown in the example below.

Example

These hypothetical data are from a laborer who reported the following activities:

8 hr of sleep 8 h x 1.0 = 8.0 8 hr of sedentary activity 9 h x 1.1 = 8.8 2 hr of slight activity 2 h x 1.5 = 3.0 3 hr of moderate activity 3 h x 2.4 = 7.2 3 hr of heavy activity 3 h x 5.0 = 15.0 Physical activity index score = 42.0

Note a person who reported sleeping and resting for 24 hr would have an index score of 24.0.

3.7.4 Statistical Analysis

3.7.4.1 Descriptive and Bivariate Analysis

Statistical analysis was done with SPSS statistical software release 12.0. Descriptive details of the anthropometric, clinical and biochemical characteristics of the study participants were computed as unadjusted means ± standard deviation (SD). Differences in the categorical variables were assessed by Chi-squared (χ 2) test with appropriate degrees of freedom. For continuous variables, differences between the groups were assessed by analysis of variance (ANOVA) or Student‟s t test where appropriate.

3.8 Feedback to Participants

Participants were provided with feedback on the anthropometric measurements, blood pressure and fasting capillary blood glucose during the survey. The physician was available to explain any significantly abnormal results which required immediate advice or advice regarding follow up.

After the results of the blood tests became available, these were reviewed by the Physician and a letter was sent to each participant. This letter stated the results of the test and advice about follow up.

CHAPTER 4

4. RESULTS

4.1 Demographic Characteristics of Study Population

One thousand and twenty four Tongans aged 15 years and older participated in the study. Of these individuals, some information was incomplete for 8 participants and they were excluded. The remaining one thousand and sixteen, 431 (48.4%) males and 585 (57.6%) females, are included in this report.

4.1.1 Age and Sex Characteristics

The age and sex characteristics of the study population are shown in Table 4.1 and Figure 4.1. Sixty eight percent of the study population was in the age group 25–54 years, 269 (62%) males and 419 (72%) females. Sixty one percent of the study participants were ≥ 35 years of age.

Table 4.1: Age and sex characteristics of study population

Variables Male Female All Age Groups No % No % No % (years) 15 – 24 51 11.8 83 14.2 134 13.2 25 – 34 94 21.8 149 25.5 243 23.9 35 – 44 96 22.3 150 25.6 246 24.2 45 – 54 79 18.3 120 20.5 199 19.6 55 – 64 72 16.7 57 9.7 129 12.7 ≥ 65 39 9.0 26 4.4 65 6.4 Total 431 48.5 585 57.8 1016 100 Data are in numbers and %.

Figure 4.1: Age-sex characteristics of study population

30 Female Male

15 Percent (%) Percent

0 15-24. 25-34 35-44 45-54 55-64 65+

10 years age group

4.1.2 Geographic Location of Study Population

These subjects were randomly selected from the three main island groups in the Kingdom of Tonga. Thirty seven percent (160 males, 249 females) from the Ha‟apai and Vava‟u island groups and 63% (271 males, 336 females) from the main island of Tongatapu, as shown in Table 4.2.

4.1.3 Occupation and Working Status of Study Population

Occupation status was classified as professional, labourer, domestic and students as discussed in the methodology (Section 3.7.3.).

Sixty seven percent of participants were engaged in domestic work (231 males, 398 females). Twenty nine percent were working in a paid occupation of which 21% were

classified as professionals (89 males, 111 females) and 8% as labourers (52 males, 22 female). Students made up 4% of the study population (13 males, 22 females).

Table 4.2: Demographic characteristics of study population

Variables Male Female All No % No % No % Geographic Location

Vava‟u and 160 37.1 249 42.6 409 40.3 Ha‟apai Tongatapu 271 62.9 336 57.4 607 59.7

Occupation and working status Professional 89 23.1 111 20.1 200 21.3

Labourer 52 13.5 22 4.0 74 7.9

Domestic 231 60.0 398 72.0 629 67.1

Students 13 3.4 22 4.0 35 3.7

Religion Free Wesleyan Church 436 42.9

Roman Catholic 109 10.7

Latter Day Saints 119 11.7

Free Church of Tonga 260 25.6

2 2 Others 73 7.2

3 3 Unknown 19 1.9 Data are in numbers and %.  Based on total number of 938 (385 males, 553 females) who stated a main job 2 Combined minor church included Tokaikolo, SDA and Bahai 3 Participants who did not complete this section

4.1.4 Religious Distribution of Study Population

Most participants, 43% of the total study population, belong to the Free Weslyan Church of Tonga (FWOT) and 26% to the Free Church of Tonga (FCOT) or Church of Tonga. Later Day Saints (LDS) was the third largest congregation (12%), followed by the Roman Catholic Church (11%). The minor religions were grouped together under

“others” which included the Tokaikolo, Seventh Day Adventurist (SDA), and Bahai. About 2% of the study population did not identify with any religion.

4.2 Characteristics of Study Population by Gender

4.2.1 Anthropometric Characteristics of study population by Gender

A summary of the anthropometric characteristics of the study population is shown in Table 4.3. The mean ± SD age of study participants was 41.3 ± 14.3 years and male participants were significantly older (p<0.001) with a mean ± SD age of 43.3 ± 15.04 years and females were, on average four years younger, mean ± SD age of 39.8 ± 13.5 years. The mean ± SD height was 170.0 ± 8.1 cm, with males being significantly taller than females (175.6 ± 6.8 vs 165.9 ± 6.4 cm, p<0.001). There was no significant difference in weight between males and females (male 93.3 ± 17.4 kg vs female 93.1 ± 17.9 kg, p=0.841). The overall mean BMI for the study population were 32.3 ± 6.1 kg/m2, and was significantly lower in males compared with females (30.2 ± 5.4 vs 33.7 ± 6.2 kg/m2, p<0.001). However, males had a higher waist to hip ratio (0.90 ± 0.1 cm) than females (0.84 ± 0.1, p<0.001). The overall mean waist circumference of the study population was 99.6 ± 13.3 cm, with no significant difference between males and females (99.2 ± 13.4 vs 99.8 ± 13.3 cm, p=0.516).

The mean percentage of body fat was 33.8 ± 11.4% for the whole study population, and was significantly higher in females than males (41.2 ± 6.7 vs 23.3 ± 23.3%, p<0.001).

Table 4.3 Anthropometric characteristics of study population by gender

Variables Female Male All n 585 431 1016 Age (years) 39.8 13.5 43.3  15.04 41.3  14.3

 BMI (kg/m2) 33.7  6.2 30.2  5.4 32.3  6.1 Height (cm) 165.9 ± 6.4 175.6 ± 6.8 170.0 ± 8.1 Weight (kg) 93.1  17.9 93.3  17.4 93.2  17.7 Waist circumference (cm) 99.8  13.3 99.2  13.4 99.6  13.3 Waist to Hip Ratio (WHR) 0.84  0.1 0.90  0.1 0.87  0.08 Percent body fat (%) 41.2  6.7  23.3  7.8 33.8  11.4

Data are means  SD and %. Significant differences between male and females at  p 0.001

4.2.2 Clinical and Metabolic Characteristics of study population by Gender

Details of clinical and metabolic characteristics of the study population for males and females are shown in Table 4.4. The overall mean ± SD systolic and diastolic blood pressures were 129.5 ± 19.2 mmHg and 80.5 ± 11.1 mmHg, respectively. Males had higher blood pressure than females, both for systolic (133.3 ± 18.6 vs 126.7 ± 19.2 mmHg, p<0.001) and diastolic blood pressure (81.5 ± 11.2 vs 79.8 ± 10.9 mmHg, p=0.012).

The overall mean ± SD total cholesterol level was 5.0 ± 1.1 mmol/L, HDL cholesterol 1.1 ± 0.3 mmol/L, triglycerides 1.3 ± 0.9 mmol/L, calculated LDL cholesterol 3.4 ± 0.9 mmol/L and total cholesterol to HDL cholesterol ratio 4.8 ± 1.4. Males had significantly higher lipid levels compared with females - total cholesterol 5.2 ± 1.1 vs 4.9 ± 1.1 mmol/L, p<0.001, triglycerides 1.5 ± 1.1 vs 1.1 ± 0.7 mmol/L, p<0.001, calculated LDL cholesterol 3.5 ± 1.0 vs 3.3 ± 0.9 mmol/L, p=0.002 and total cholesterol to HDL cholesterol ratio 5.1 ± 1.4 vs 4.6 ± 1.3, p<0.001. On the other hand, HDL cholesterol levels were similar in males 1.1 ± 0.3 mmol/L and females 1.1 ± 0.3 mmol/L.

The mean ± SD creatinine level of the study population was 0.08 ± 0.2 mmol/L and urinary microalbumin level was 1.4 ± 2.4 mg/mmol. Creatinine level was significantly higher in males than females (0.09 ± 0.02 vs 0.07 ± 0.01mmol/L, p<0.001) but there

was no significant difference in urine albumin/creatinine ratio (1.6 ± 2.8 vs 1.3 ± 2.0 mg/mmol, p=0.111).

Table 4.4 Clinical and metabolic characteristics of study population by gender

Female Male All N 585 431 1016 Systolic blood pressure (mmHg) 126.7  19.2 133.3  18.6* 129.5 ± 19.2 Diastolic blood pressure (mmHg) 79.8 10.9 81.5  11.2£ 80.5 ± 11.1 Total cholesterol (mmol/L) 4.9  1.1 5.2  1.1 * 5.0 ± 1.1 HDL cholesterol (mmol/L) 1.1  0.3 1.1 0.3 £ 1.1 ± 0.3 Triglycerides (mmol/L) 1.1  0.7 1.5  1.1 * 1.3 ± 0.9 Calculated LDL (mmol/L) 3.3  0.9 3.5  1.0 £ 3.4 ± 0.9 Total Cholesterol/HDL Ratio 4.6  1.3 5.1  1.4* 4.8 ± 1.4 Creatinine (mmol/L) 0.07 ± 0.01 0.09 ± 0.02* 0.08 ± 11.1 ACR (mg/mmol) 1.3  2.0 1.6  2.8 1.4 ± 2.4 Data are mean  SD. Significant difference between male and female at * p<0.001 and £ p<0.05 or less

4.2.3 Nutrient Intake of study population by Gender

A summary of study participants‟ nutrient intake by gender is presented in Table 4.5. The overall mean ± SD total energy intake was 4855.8 ± 2304.4 kcal. Males consumed significantly more than females (5308.4 ±2366.4 vs 4522.3 ± 2201.1 kcal, p=0.009). Mean energy intake included 177.4 ± 96.7g of protein, 121.3 ± 72.5g of fat and 751.3 ± 396.1g of CHO. Mean intake was significantly higher in males than females for protein (193.5 ± 97.2 vs 165.5 ± 94.7 g, p0.001), total fats (131.2 ± 72.6 vs 114.0 ± 71.6g, p0.001) and CHO (819.1 ± 410.0 vs 701.3 ± 378.1g, p0.001). When macronutrients were considered as percentage of energy, the mean contribution to total energy was 15.2 ± 4.6% protein, 22.3 ± 8.0% total fats and 58.7 ± 10.9% CHO with no significant difference between males and females. The mean alcohol intake was 3.4 ± 16.3g and males consumed significantly more than females (7.0 ± 23.6 vs 0.8 ± 6.0 g, p<0.001).

Saturated (SFA) and monounsaturated (MUFA) fats were the major contributors to the mean total fat intake. The mean ± SD SFA fat intake was 49.7 ± 29.5g, MUFA 42.5 ± 28.6g and PUFA was 13.5 ± 9.4g. Males consumed significantly more SFA fat (54.0 ± 29.9 vs 46.6 ± 71.6g) and MUFA (46.2 ± 28.7 vs 39.8 ± 28.2g, p<0.001) than females. There was no significant difference in PUFA (14.5 ± 9.4 vs 13.4 ± 9.3g, p=0.062)

intake. The mean ± SD cholesterol intake was 520.8 ± 349.7mg and was significantly higher in males than females (573.4 ± 350.8 vs 482.0 ± 344.1 mg, p0.001).

Starch was the major contributor to the total CHO intake. The study population mean ± SD intake of starch was 549.5 ± 330.0g, dietary fibre 67.3 ± 32.2g and total sugar 201.7 ± 149.8 g. Overall males consumed significantly more starch (602.8 ± 336.4 vs 510.3 ± 319.8 g, p<0.001), dietary fibre (71.2 ± 31.6 vs 64.5 ± 32.6 g, p<0.001) and total sugar (216.3 ± 171.0 vs 191.0 ± 131.1 g, p<0.001) than females.

Table 4.5  Nutrient intake of study population by gender

Female Male All n 585 431 1016 Energy (kcal) 4522.3  2201.0 5308.4  2366.2£ 4855.8  2304.4 Protein(g) 165.5  94.7 193.5  97.2* 177.4  96.7 Total Fat(g) 114.0  71.6 131.2  72.6* 121.3  72.5 Carbohydrate(g) 701.3  378.1 819.1  410.0* 751.3  396.1 Energy from Protein(%) 15.1  4.7 15.2  4.4 15.2  4.6 Energy from Fat (%) 22.4  8.0 22.2  8.0 22.3  8.0 Energy from CHO (%) 58.9  10.8 58.3  10.9 58.7  10.9 Alcohol (g) 0.8  6.0 7.0  23.6* 3.4  16.3 SFA fat (g) 46.6  71.6 54.0  29.9* 49.7  29.5 MUFA fat(g) 39.8  28.2 46.2  28.7 42.5  28.6 PUFA fat(g) 13.4  9.3 14.5  9.4 13.9  9.4 Cholesterol(mg) 482.0  344.1 573.4  350.8* 520.8  349.7 Starch(g) 510.3  319.8 602.8  336.4* 549.5  330.0 Dietary Fibre(g) 64.5  32.6 71.2  31.6£ 67.3  32.2 Total Sugars(g) 191.0  131.1 216.3  171.0£ 201.7  149.8 Data are mean  SD. Significant difference between males and females at * p<0.001 and £ p<0.05

4.2.4 Lifestyle Behaviours of study population by Gender

Details of lifestyle behaviours of the study population by gender are shown on Table 4.6.

The mean smoking and alcohol consumption rates indicated that 28.5% of study participants smoked and 12.9% consumed alcohol. More than half of the male

participants (52.9%) smoked compared with 10.6% of females, and 30% of males drank alcohol compared with 4% of female participants.

Table 4.6: Lifestyle behaviours of study population by gender

Female Male All N 585 431 1016 Cigarette smoking (%) 10.6 52.9* 28.5 Alcohol consumption (%) 3.6 25.9* 12.9 Traditional Medicine usage (%) 67.3 57.8£ 63.1 Physical Activity 28.6  2.8 33.0 ± 6.7* 30.4 ± 5.3 Physical Activity2 10.5  5.7 13.6  8.3* 13.6  8.3 Data are % and means  SD unless indicated. Significant difference between males and females at * p<0.001 and £ p<0.05 1Physical activity level in 24 hour period 2 Physical activity level in active hours only

The use of traditional medicine was very common with 63% of study participants reporting use of some kind of traditional medicine. This was more common in females (68%) than males (58%, p=0.002).

Males reported being more physically active than females, both in a 24 hour period (33.0 ± 6.7 vs 28.6  2.8, <0.001) and in active hours (13.6 ± 8.3 vs 10.5  5.7, <0.001).

4.3 Characteristics of Study Population by Age Groups

4.3.1 Anthropometric characteristics of study population by age groups

The anthropometric characteristics by age group of study participants are shown in Table 4.7.

Body Mass Index (BMI) was significantly influenced by age. The lowest BMI was in the younger age groups of 15–25 years (27.7 ± 4.6 kg/m2), peaked in the 45-54 year age group (33.9 ± 5.9 kg/m2), then declined in the older age groups. Weight followed the same pattern being lowest in the 15-24 year age group (80.7 ± 13.7 kg), highest in the 35–44 year age group (97.0 ± 16.8 kg) and decreasing thereafter. Waist circumference increased with age, with only small differences after age 35-44 years.

Waist to Hip ratio increased significantly (p<0.001) with age. The most significant increase (p<0.001) was between the 15–24 year (0.80 ± 0.06) and 25-34 year age groups (0.85 ± 0.7) and then gradually increased to the highest value (0.92 ± 0.10) in the 65 years and older age groups.

Table 4.7: Anthropometric characteristics of study population by age groups

Age of participants 1524 2534 3544 4554 5564 65 p n 134 243 246 199 129 65 BMI (kg/m2) 27.7  4.6 32.6  6.1 33.6  6.1 33.9  5.9 32.2  6.3 30.3  5.1 0.001 Weight (kg) 80.7  13.7 95.2  17.0 97.0  16.8 96.9  18.0 92.7  18.0 85.9  15.4 0.001 WC (cm) 86.4  10.2 98.3  12.7 102.1  12.0 103.4  11.2 103.3  13.7 102.7  14.0 0.001 WHR 0.80  0.06 0.85  0.07 0.87  0.07 0.89  0.07 0.91  0.08 0.92  0.10 0.001 % Body fat 29.9  11.9 34.4  12.5 35.3  10.7 35.6  10.3 31.9  10.8 29.8  10.8 0.001 Data are means  SD . WC – waist circumference; WHR – waist to hip ratio

The percentage of body fat increased with age, peaking in the 45–54 year age group (35.6 ± 10.3%) then declined in the older groups with the result in those aged 65 years and older being similar to the 15-24 year age group.

4.3.2 Anthropometric characteristics of study population by age and gender

Data are presented in Table 4.8 and Figures 4.2 – 4.5.

The age specific data indicate that males in the youngest age group had the lowest mean ± SD values for BMI (20.2 ± 26.3 kg/m2), weight (82.6 ± 15.1 kg), waist to hip ratio (0.8 ± 0.05), but the highest value for height (177.2 ± 6.3 cm). In males, age 35 to 54 was associated with the highest mean weight, BMI, waist circumference and highest percentage of body fat. The WHR was highest in the 65 years and older age groups (1.0 ± 0.1).

The pattern was fairly similar in females. The age group 45-54 years was associated with the highest BMI, weight and WHR. Percentage of body fat was highest (42.0 ± 6.5 %) in the 25-34 years old group. The older age groups, 55-64 years, had the highest waist circumference (104.9 ± 15.1 cm).

Females had a higher BMI compared with males across all age groups.

Table 4.8: Age specific anthropometric characteristics of study population by gender

Male 1524 2534 3544 4554 5564 65.0 n 51 94 96 79 72 39 BMI (kg/m2) 26.4 ± 6.3 30.6 ± 5.5 31.5 ± 5.2 31.6 ± 5.3 30.1 ± 4.9 29.2 ± 4.4 Height (cm) 177.2 ± 6.3 176.6 ± 8 .9 176.7 ± 5.7 175.1 ± 5.2 173.7 ± 6.0 172.6 ± 6.3 Weight (kg) 82.6 ± 15.1 95.1 ± 16.7 98.3 ± 16.8 97.0 ± 18.2 90.9 ± .16.8 87.2 ± 14.9 WC (cm) 86.1 ± 9.9 96.9 ± 12.2 101.9 ± 12.2 103.2 ± 12.3 101.9 ± 12.4 102.4 ± 15.3 WHR 0.8 ± 0.05 0.9 ± 0.05 0.9 ± 0.05 0.9 ± 0.05 0.9 ± 0.07 1.0 ± 0.1 Body fat (%) 17.2 ± 7.9 20.5 ± 8.1 25.3 ± 7.3 25.6 ± 7.1 23.6 ± 6.5 23.5 ± 8.1 Female 1524 2534 3544 4554 5564 65.0 n 83 149 150 120 57 26 BMI (kg/m2) 28.6 ± 4.3 34.0 ± 6.2 34.9 ± 5.6 35.4 ± 5.9 34.9 ± 6.8 31.9 ± 5.7 Height (cm) 166.7 ± 2.8 167.6 ± 5.6 165.4 ± 7.8 165.1 ± 5.6 164.8 ± 6.2 162.3 ± 6.4 Weight( kg) 79.5 ± 12.8 95.3 ± 17.2 96.2 ± 16.9 96.7± 17.9 94.9 ± 19.4 84.0 ± 16.0 WC (cm) 86.6 ± 10.4 99.2 ± 13.1 102.2 ± 12.0 103.5 ± 10.4 104.9 ± 15.1 103.0 ± 12.1 WHR 0.8 ± 0.06 0.8 ± 0.06 0.8 ± 0.07 0.9 ± 0.06 0.9 ± 0.09 0.9 ± 0.1 Body fat (%) 37.5 ± 5.9 42.0 ± 6.5 41.6 ± 7.2 41.9 ± 6.1 41.0 ± 6.3 38.5 ± 7.6 Data are means  SD. WC – waist circumference; WHR – waist to hip ratio

Figure 4.2: Body Mass Index of study population by age and gender

Male 30 Female BMI (kg/m2) BMI

20 15 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 Age groups (years)

Figure 4.3: Weight of study population by age and gender

100

80 MeanWeight (kg)

Male Female

70 15-24 25-34 35-44 45-54 55-64 ³65 Age groups (years)

Figure 4.4: Waist circumference of study population by age and gender

110 Mean (cm) Mean 90

Female Male

70 15-24 25-34 35-44 45-54 55-64 ³65 Age groups (years)

Figure 4.5: Percentage of body fat of study population by age and gender

Male Feamle BodyFat (%)

15 15-24 25-34 35-44 45-54 55-64 ³65 Age groups (years)

4.3.3 Clinical and Metabolic Characteristics of study population by Age Groups

The clinical and metabolic characteristics of the study population are shown on Table 4.9.

Both systolic and diastolic blood pressure increased steadily and significantly (p<0.001) with age. The lowest systolic (119.6 ± 14.6 mmHg) and diastolic blood pressures (75.3 ± 9.6 mmHg) were in the younger age groups (15–24 years) and the highest levels in the older age groups (65 years and older) (147.9 ± 25.1 and 85.5 ± 12.8 mmHg).

Total cholesterol and calculated LDL levels increased significantly (p<0.001) with age. The younger age groups 15-24 years had the lowest level of total cholesterol (4.3 ± 1.1 mmol/L) and calculated LDL cholesterol (2.8 ± 1.0 mmol/L). Triglycerides and total cholesterol to HDL cholesterol ratio increased until age 55-64 then declined slightly. HDL cholesterol decreased slightly from the youngest age group and was then similar across the age groups.

The creatinine and microalbumin levels increased significantly (p<0.001) with age, being highest in the oldest age group.

Table 4.9: Clinical and metabolic characteristics of the study population by age groups

Age of participants 1524 2534 3544 4554 5564 65.0 P N 134 243 246 199 129 65 SBP (mmHg) 119.6  14.6125.3  15.8127.9  18.1 131.2  17.3 138.5  21.0 147.9  25.1 0.001 DBP (mmHg) 75.3  9.6 79.4  10.4 80.4  10.9 82.2  10.5 82.9  11.7 85.5  12.8 0.001 Total chol (mmol/L) 4.3  1.1 4.9  1.0 5.1  1.0 5.3  1.0 5.4  1.1 5.4  1.0 0.001 HDL chol (mmol/L) 1.2  0.3 1.1  0.3 1.1  0.3 1.0  0.3 1.1  0.3 1.1  0.3 0.001 TG (mmol/L) 0.9  0.5 1.2  0.9 1.3  1.0 1.4  1.0 1.5  1.1 1.4  0.8 0.001 LDL (mmol/L) 2.8  1.0 3.2  0.8 3.4  0.9 3.6  0.9 3.7  0.9 3.7  0.9 0.001 TChol:HDL Ratio 3.8  1.0 4.5  1.1 4.8  1.3 5.2  1.3 5.4  1.5 5.2  1.3 0.001 Creatinine (mmol/L) 0.07  0.01 0.08  0.02 0.08  0.02 0.08  0.02 0.09  0.02 0.09  0.02 0.001 ACR (mg/mmol) 0.9  0.8 1.2  2.0 1.5  2.1 1.5  2.1 2.0  3.6 2.1  3.2 0.001 Data are means  SD unless indicated. SBP – systolic blood pressure; DBP – diastolic blood pressure; ACR – Albumin Creatinine Ratio

4.3.4 Clinical and Metabolic Characteristics of study population by Age and Gender

The clinical and metabolic characteristics of the study population by age and gender are shown in Table 4.10.

Systolic blood pressure increased with increasing age in both males and females. The same general pattern was observed for diastolic blood pressure, although there was some minor variation in this trend. Total cholesterol and triglycerides peaked in the 45- 54 year age group in males and in the 55-64 year age group in females. HDL cholesterol was similar across age groups in both males and females. Creatinine increased with increasing age in both males and females and the same tendency was observed for microalbuminuria.

Table 4.10: Clinical and Metabolic characteristics of study population by age and gender Age of participants Male 1524 2534 3544 4554 5564 65.0 p n 51 94 96 79 72 39 SBP (mmHg) 124.2  13.2 131.5  16.0 131.0  14.4 133.4  18.9 135.6  18.0 150.6  27.1 0.001 DBP (mmHg) 76.4  10.8 81.4  10.0 81.4  10.7 82.9  10.2 80.8  11.9 86.8  13.6 0.001 Total chol (mmol/L) 4.1  1.0 5.1  1.0 5.4  1.0 5.6  1.0 5.3  1.1 5.3  1.1 0.001 HDL chol (mmol/L) 1.1  0.3 1.1  0.3 1.1  0.2 1.0  0.2 1.1  0.3 1.1  0.3 0.001 TG (mmol/L) 1.0  0.6 1.5  1.2 1.7  1.3 1.7  1.1 1.4  1.0 1.2  0.6 0.001 LDL (mmol/L) 4.1  1.0 5.1  1.0 5.4  1.0 5.6  1.1 5.3  1.1 5.3  1.1 0.001 TChol:HDL Ratio 3.9  1.1 4.8  1.2 5.3  1.4 5.7  1.4 5.3  1.3 5.2  1.5 0.001 Creatinine (mmol/L) 0.08  0.01 0.09  0.01 0.09  0.01 0.09 ± 0.01 0.1  0.02 0.1 ± 0.02 0.001 MA (mg/mmol) 0.9  1.1 1.1  1.6 1.6  2.4 1.7 ± 2.7 2.4  4.6 2.0 ± 3.2 0.001 Female 1524 2534 3544 4554 5564 65.0 p n 83 149 150 120 57 26 SBP (mmHg) 116.8 ± 14.8 121.4 ± 14.4 126.0 ± 19.9 129.7 ± 16.1 142.1 ± 23.9 143.8 ± 21.6 0.001 DBP (mmHg) 74.6 ± 8.8 78.1 ± 10.5 79.8 ± 11.1 82.7 ± 10.7 85.4 ± 11.0 83.5 ± 11.5 0.001 Total chol (mmol/L) 4.4 ± 1.2 4.7 ± 1.0 4.9 ± 1.0 5.0 ± 0.9 5.6 ± 1.1 5.5 ± 0.9 0.001 HDL chol (mmol/L) 1.2 ± 0.2 1.1 ± 0.2 1.1 ± 0.2 1.1 ± 0.3 1.1 ± 0.3 1.1 ± 0.2 0.001 TG (mmol/L) 0.9 ± 0.4 1.0 ± 0.6 1.0 ± 0.6 1.2 ± 0.7 1.6 ± 1.5 1.5 ± 1.0 0.001 LDL (mmol/L) 4.4 ± 1.2 4.7 ± 1.0 4.9 ± 1.0 5.0 ± 0.9 5.6 ± 1.1 5.5 ± 0.9 0.001 TChol:HDL Ratio 3.8 ± 1.0 4.3 ± 1.0 4.5 ± 1.2 4.9 ± 1.1 5.5 ± 1.7 5.3 ± 1.1 0.001 Creatinine (mmol/L) 0.06 ± 0.01 0.07 ± 0.01 0.07 ± 0.01 0.07 ± 0.01 0.1 ± 0.02 0.1 ± 0.01 0.001 ACR (mg/mmol) 0.9 ± 0.5 1.3 ± 2.2 1.4 ± 2.3 1.4 ± 1.5 1.5 ± 1.5 2.2 ± 3.3 0.001 Data are means  SD unless indicated. Significant difference between age groups at p<0.001 and p<0.05 SBP – systolic blood pressure; DBP – diastolic blood pressure; ACR – albumin creatinine ratio

4.3.5 Nutrient Intake of study population by Age Groups.

Details of nutrient intake by age group are shown in Table 4.11.

The mean ± SD total energy intake decreased significantly with increasing age (p<0.001). Those aged 15-24 years had the highest energy intake (5472.0 ± 2336.5 kcal) and the lowest energy intake (4056.7 ± 1638.2 kcal) was observed in people 65 years and older. Macronutrient intake (protein, fat and CHO) followed a similar pattern. However when protein intake was considered as percent contribution to total energy intake, no significant difference across age groups was observed (p=0.086).

The intake of specific fats reflected total fat intake with amounts of SFA, MUFA and PUFA decreasing with increasing age. There was a trend to small reductions in contribution of fat to total energy intake with increasing age.

For total CHO intake there was a trend of increasing contribution to total energy intake with increasing age. Starch was the largest single contributor to CHO intake and decreased with age (p=0.007). Total sugars intake from all sources was highest (217.8 ± 163.0 g) in the 15–24 age groups then declined with age. Dietary fibre intake was highest in the youngest age group but there was no significant trend across age groups. The mean ± SD intake of alcohol was highest (8.0 ± 28.4g) in the 15–24 years and decreased significantly (p=0.001) with increasing age being lowest (0.1 ± 0.4g) in the 65 years and older age group.

Table 4.11: Nutrient intake of study population by age groups

Age of participants 1524 25.034 3544 4554 5564 65.0 P n 134 243 246 199 129 65 Energy (kc) 5472.0  2336.5 5323.7  2618.2 4701.7  2073.1 4760.0  4756.0 4178.5  4178.5 4056.7  1638.2 0.001 Protein (g) 195.4  103.4 199.0  103.4 177.5  92.6 165.5  84.8 149.9  73.7 149.6  62.2 0.001 Total Fat (g) 148.3  86.6 138.4  81.6 119.1  66.7 109.1  62.1 97.3  56.4 95.2  46.7 0.001 SFA (g) 61.6  34.8 56.9  32.6 48.7  27.4 44.5  25.4 39.6  23.3 38.1  19.3 0.001 MUFA (g) 52.7  34.3 49.2  32.3 41.9  26.4 37.2  24.5 33.2  21.9 33.5  19.0 0.001 PUFA (g) 16.3  12.2 15.2  9.6 13.8  8.7 13.1  8.8 11.6  7.9 10.8  6.7 0.001 Chol (g) 604.2  388.1 602.1  414.7 519.5  388.3 467.3  295.4 420.8  265.7 411.2  214.9 0.001 CHO (g) 819.0  367.5 805.4  423.7 718.9  368.1 769.7  446.2 666.6  351.5 643.5  307.7 0.001 D/Fibre (g) 71.7  29.5 69.8  36.9 65.7  30.7 68.1  34.4 62.02  26.9 63.7  27.3 0.115 T/Sugars (g) 217.8  163.0 212.5  153.9 192.8  145.0 216.9  177.6 177.8  100.1 162.6  162.6 0.019 Starch (g) 601.0  291.3 592..9  366.3 526.1  488.8 552.8  302.7 488.8  302.7 480.9  267.6 0.007 Alcohol (gm) 8.0  28.4 5.0  19.6 2.9  13.9 1.8  7.9 1.0  6.6 0.1  0.4 0.001 E Protein (%) 14.5  3.9 15.3  4.5 15.7  5.0 14.7  4.4 15.0  4.6 15.6  4.8 0.086 E Fat (%) 23.9  7.9 23.0  7.8 22.7  7.9 21.2  8.0 20.7  8.0 21.4  8.3 0.003 E CHO (%) 57.4  10.5 57.8  10.8 57.7  11.3 60.4  10.8 60.5  10.6 59.4  10.4 0.012 Data are means  SD. D/Fibre – dietary fibre; T/Sugars – total sugars ; E - energy

4.3.6 Lifestyle behaviour of study population by Age Groups

Details of lifestyle behaviours of the study population by age groups are shown on Table 4.12.

The percentage of people smoking cigarettes was similar across age groups (p=0.537). The percentage of people consuming alcohol was highest in the 15-24 year age group and then decreased with increasing age. Use of traditional medicine increased significantly (p<0.001) with increasing age being the highest in the older age groups of  65.0 years with 82% using some kind of traditional medicine.

The level of physical activity was similar across age groups, both over 24 hrs and for active hours only.

Table 4.12: Lifestyle behaviours of study population by Age Groups

Age of participants 1524 2534 3544 4554 5564 65 P n 134 243 246 199 129 65 Cigarette smoking (%) 29.1 24.3 29.1 31.7 27.9 33.8 0.537 Alcohol (%) 21.1 16.9 11.9 10.6 6.2 7.7 0.002 Traditional Medicine (%) 41.0 58.8 65.4 70.9 68.2 81.5 0.001 Physical Activity 1 30.0  5.7 30.2  5.7 30.2  4.6 30.5  5.0 31.2  5.5 31.2  5.2 0.359 Physical Activity 2 9.8  6.7 11.9  7.8 11.9  6.4 12.0  6.7 12.6  7.1 11.9  7.2 0.049 Data were means  SD and % unless if indicated. 1Physical activity level over 24 hours 2Physical activities level for active hours only

4.4 Characteristics of study population by Geographic Location

4.4.1 Anthropometric Characteristics of study population by Geographic Location

The anthropometric characteristics of the study population by geographic location are presented on Table 4.13.

The participants from Ha‟apai/Vava‟u were significantly older than the Tongatapu participants (44.2 ± 13.1 vs 39.6 ±14.7 years, p0.001), heavier (BMI 33.2 ± 6.2 vs 31.6 ± 5.9 kg/m2, p<0.001, weight 95.6 ± 17.9 vs 91.5 ± 17.4 kg, p<0.001) and had a larger waist circumference (101.0 ± 13.5 vs 98.6 ± 13.1 cm, p=0.004) and waist to hip ratio (0.88 ± 0.1 vs 0.86 ± 0.1, p=0.001).

The percentage of body fat was similar between the Ha‟apai/Vava‟u and Tongatapu participants (34.2 ± 11.1 vs 33.3 ± 11.7, p=0.291).

Table 4.13: Anthropometric characteristic of study population by geographic location

Ha’apai/Vava’u Tongatapu P n 409 607 Age (years) 44.2  13.1 39.6  14.7 0.001

Body Mass Index (kg/m2) 33.2  6.2 31.6  5.9 0.001 Weight (kg) 95.6  17.9 91.5  17.4 0.001 Waist circumference (cm) 101.0  13.5 98.6  13.1 0.004 Waist hip ratio 0.88  0.1 0.86  0.1 0.001 Percent body fat 34.2  11.1 33.3  11.7 0.291 Data are means  SD.

4.4.2 Clinical and Metabolic Characteristics of study population by Geographic Location

The clinical and metabolic characteristics of the study population by geographic location are shown in Table 4.14. Systolic blood pressure was significantly higher in the Tongatapu than the Ha‟apai/Vava‟u participants (130.8 ± 20.5 vs 127.4 ± 17.0 mmHg, p=0.005) but there was no significant difference in diastolic blood pressure (81.0 ± 11.8 vs 79.8 ± 9.8 mmHg, p=0.15).

Tongatapu participants had a significantly higher level of total cholesterol (5.2 ± 1.1 vs 4.8 ± 1.0 mmol/L, p<0.001), HDL cholesterol (1.1 ± 0.3 vs 1.0 ± 0.3 mmol/L, p<0.001), triglycerides (1.4 ± 1.0 vs 1.2 ± 0.7 mmol/L, p=0.001) and calculated LDL cholesterol (3.4 ± 1.0 vs 3.3 ± 0.9 mmol/L, p=0.007) than the Ha‟apai/Vava‟u participants. However, total cholesterol to HDL cholesterol ratio was similar between the Tongatapu and Ha‟apai/Vava‟u participants (4.8 ± 1.3 vs 4.9 ± 1.4, p=0.153).

Creatinine was significantly higher in the Ha‟apai/Vava‟u participants than Tongatapu (0.08 ± 0.02 vs 0.07 ± 0.02 mmol/L, p0.001) with no significant difference observed in microalbumin level (1.5 ± 2.5 vs 1.4 ± 2.3 mg/mmol, p=0.783).

The percent of participants reporting having a family member with diabetes was similar in Tongatapu (29.8%) and Ha‟apai/Vava‟u (28%) (p=0.658).

Table 4.14: Clinical and metabolic characteristics of the study population by geographic location

Ha’apai/Vava’u Tongatapu P n 409 607 Systolic blood pressure (mmHg) 127.4  17.0 130.8  20.5 0.005 Diastolic blood pressure (mmHg) 79.8  9.8 81.0  11.8 0.105 Total cholesterol (mmol/L) 4.8  1.0 5.2  1.1 0.001 HDL cholesterol (mmol/L) 1.0  0.3 1.1  0.3 0.001 Triglycerides (mmol/L) 1.2  0.7 1.4  1.0 0.001 Calculated LDL (mmol/L) 3.3  0.9 3.4  1.0 0.007 Total Cholesterol:HDL Ratio 4.9  1.4 4.8  1.3 0.153 Microalbumin (mg/mmol) 1.5  2.5 1.4  2.3 0.783 Creatinine (mmol/L) 0.08  0.02 0.07  0.02 0.001 Family history of diabetes (%) 28.3 29.8 0.658 Data are means  SD unless indicated.

4.4.3 Nutrient Intake of study population by Geographic Location

Details of the nutrient intake of the study population by location are shown in Table 4.15.

Overall, the Tongatapu participants‟ mean ± SD nutrient intake was significantly higher in total calories (5314.1 ± 2416.2 vs 4175.5 ± 1939.9 kcal, p0.001), protein (144.4 ± 75.0 vs 87.0 ± 52.3g, p0.001), total fat (144.4 ± 75.0 vs 87.0 ± 52.3g, p0.001), SFA (59.5 ± 30.1 vs 35.1 ± 21.5g, p0.001), MUFA (51.5 ± 30.0 vs 29.2 ± 20.2g, p0.001), PUFA (16.3 ± 10.1 vs 10.2 ± 6.7g, p0.001), cholesterol (593.3 ± 374.0 vs 413.0 ± 277.6 mg, p0.001), CHO (791.3 ± 413.6 vs 692.0 ± 360.9g, p0.001), dietary fibre (70.6 ± 34.6 vs 62.5 ± 360.9g, p0.001), starch (586.4 ± 343.8 vs 494.9 ± 300.5 g, p0.001), and alcohol (5.1 ± 200 vs 1.0 ± 7.7g, p0.001) than the Ha‟apai /Vava‟u participants. The consumption of total sugar was similar between the two groups (204.8 ± 155.9 vs 197.1 ± 140.3g, p=0.424).

When contribution of macronutrients to energy was considered, Tongatapu participants mean ± SD energy intake was significantly higher in protein (15.6 ± 4.5 vs 14.6 ± 4.6%,

p0.001) and fats (24.5 ± 7.3 vs 19.1 ± 7.9%, p0.001) but lower in CHO (62.3 ± 10.8 vs 56.2 ± 10.3%, p0.001) compared with the Ha‟apai/Vava‟u participants.

Table 4.15: Nutrient intake of study population by geographic location

Ha’apai /Vava’u Tongatapu P n 409 607 Energy (kc) 4175.5  1939.9 5314.1  2416.2 0.001 Protein (g) 145.2  76.1 199.1  103.0 0.001 Total Fat (g) 87.0  52.3 144.4  75.0 0.001 Saturated Fat (g) 35.1  21.5 59.5  30.1 0.001 MUFA (g) 29.2  20.2 51.5  30.0 0.001 PUFA (g) 10.2  6.7 16.3  10.1 0.001 Cholesterol (mg) 413.0  277.6 593.3  374.0 0.001 CHO (g) 692.0  360.9 791.3  413.6 0.001 Dietary Fibre (g) 62.5  28.0 70.6  34.6 0.001 Total Sugars (g) 197.1  140.3 204.8  155.9 0.424 Starch (g) 494.9  300.5 586.4  343.8 0.001 Alcohol (gm) 1.0  7.7 5.1  20.0 0.001 Energy from Protein (%) 14.6  4.6 15.6  4.5 0.001 Energy from Fat (%) 19.1  7.9 24.5  7.3 0.001 Energy from CHO (%) 62.3  10.8 56.2  10.3 0.001 Data are means  SD.

4.4.4 Lifestyle behaviour of study population by Geographic Location

Details of lifestyle behaviour of the study population by location are shown in Table 4.16.

Cigarette smoking was significantly more common in the Tongatapu participants than in the Vava‟u/Ha‟apa participants (31.5 vs 24.3%, p=0.015) as well as the percent who consumed alcohol (18.4 vs 5.1%, p<0.001).

The level of physical activity was similar between the Ha‟apai/Vava‟u and Tongatapu participants, if calculated on 24 hours activities (30.3 ± 4.9 vs 30.5 ± 5.5, p=0.729) but slightly higher in Vava‟u/Ha‟apai participants if based on active hours (12.4 ± 6.9 vs

11.3 ± 7.1, p0.05). The use of traditional medicine was common with no significant difference between the participants (62.1 vs 63.8%, p=0.639)

Table 4.16: Lifestyle behaviour of study population by geographic location

Ha’apai/Vava’u Tongatapu P N 409 607 Cigarette smoking (%) 24.3 31.5 0.015 Alcohol (%) 5.1 18.4 0.001 Traditional Medicine (%) 62.1 63.8 0.639 Physical Activity 1 30.3  4.9 30.5  5.5 0.729 Physical Activity 2 12.4  6.9 11.3  7.1 0.023

Data are means  SD and % unless indicated. 1Physical activity in 24 hours, 2 Physical activity by active hours only.

4.5 Characteristics of study population by Occupation

A total of 938 participants provided information on occupation. Sixty seven percent of participants were engaged in domestic work, 29% were working in paid occupation (21% as professional and 8% as labourers). Students made up 4% of the study population (Section 4.1.3).

4.5.1 Anthropometric Characteristics of study population by Occupation

A summary of the anthropometric characteristics of the study population by occupation is shown in Table 4.17. The students were the youngest group and had the lowest weight measures, except for percent body fat. The professional and domestic participants had the highest BMI and percent body fat. The lowest percent body fat was observed in the labourer group.

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Table 4.17: Anthropometric characteristics of study population by occupation

Professional Labourer Domestic Students p

n 200 74 629 35 Age 38.5  10.7 41.7  12.2 43.7  14.6 19.0  4.9 0.001 BMI (kg/m2) 32.5  5.6 31.6  6.0 32.6  6..2 27.8  4.9 0.001 Weight (kg) 95.0  16.2 94.3  18.7 93.0  17.5 80.6  13.9 0.001 Height (cm) 171.2  8.2 172.6  7.7 169.1  7.7 170.4  7.5 0.001 Waist circumference (cm) 99.7  11.4 100.3  13.5 100.2  13.3 86.9 9.5 0.001 Waist hip ratio 0.86  0.08 0.89  0.06 0.87  0.08 0.79  0.05 0.001 Percent body fat 34.5  11.9 28.8  12.8 34.2  11.0 32.9  11.1 0.010 Family Hx of diabetes (%) 36.2 37.0 26.0 17.1 0.006 Data are means ± SD and % .

4.5.2 Clinical and metabolic characteristics of study population by Occupation

Details of clinical and metabolic characteristics of the study population by occupation are shown in Table 4.18.

Students had the most favourable and labourers the least favourable metabolic profiles. There was little difference between professionals and domestic participants except for systolic blood pressure which was lower in professionals.

The mean level of creatinine were higher in labourers and microalbumin was similar (p=0.208) throughout the occupation groups.

Table 4.18 Clinical and metabolic characteristics of study population by occupation

Professional Labourer Domestic Students p n 200 74 629 35 SBP (mmHg) 127.2  16.5 131.1  15.1 130.5  20.5 118.9  12.2 0.001 DBP (mmHg) 80.2  10.0 81.8  10.0 80.5 11.4 77.8  11.6 0.349 Total cholesterol (mmol/L) 5.0  1.0 5.1  1.2 5.0  1.1 4.4  1.4 0.010 HDL cholesterol (mmol/L) 1.1  0.3 1.0  0.2 1.1  0.3 1.1  0.2 0.022 Triglycerides (mmol/L) 1.2  0.9 1.5  1.3 1.3  0.9 0.8  0.4 0.002 Calculated LDL (mmol/L) 3.4  0.9 3.5  1.0 3.4  0.9 2.9  1.3 0.028 Total Cholesterol:HDL Ratio 4.7  1.2 5.3  1.6 4.8  1.4 3.9  1.2 0.001 Creatinine (mmol/L) 0.08  0.01 0.09  0.01 0.08  0.01 0.07  0.02 0.010 ACR (mg/mmol) 1.3  2.3 1.8  3.5 1.5  2.3 0.9  0.9 0.208 Data are means ± SD. SBP – systolic blood pressure; DBP – diastolic blood pressure;ARC: Albumin/Creatinine Ratio 101

4.5.3 Nutrient intake of study population by occupation

Details of the nutrient intake of the study population by occupation is shown in Table 4.19.

Although there were some differences in total calorie intake between different occupation groups, this was not significant (p=0.057). There were significant differences in macronutrient contribution to total energy intake. The professional participants had the highest contribution from protein (16.0 ± 4.0%) and fat (25.0 ± 6.9%) the lowest for CHO (54.8 ± 9.8%), whereas domestic participants had the lowest contribution from fat (21.0 ± 8.1%) and the highest from CHO (60.2 ± 10.8%). Professional participants had the highest intake of alcohol.

Table 4.19: Nutrient intake of study population by occupation

Professional Labour Domestic Students P n 200 74 629 35 Energy (kc) 5050.2  2367.1 4966.9  2090.8 4704.2  2219.4 5528.2  2294.1 0.057 Protein(g) 195.5  97.6 191.5  124.0 168.6  91.2 183.9  79.3 0.003 Total Fat(g) 141.6  74.3 130.8  77.0 110.2 66.6 153.3  77.6 0.001 SFA Fat(g) 57.7  29.9 53.9  32.0 45.2  27.2 62.8  30.9 0.001 MUFA9g) 51.1  28.9 46.7  31.3 37.9  26.2 55.2  31.2 0.001 PUFA (g) 16.6  10.1 14.0  8.2 12.5  8.3 17.0  11.1 0.001 Cholesterol (mg) 590.2  344.0 586.7  477.5 484.1  328.4 566.9  280.2 0.001 Carbohydrate(g) 731.4  371.5 744.9  323.2 748.6  397.1 845.3  386.5 0.458 Dietary Fibre(g) 65.6  31.2 64.9  27.1 68.1  32.4 74.1  35.5 0.412 Total Sugars(g) 206.9  162.7 203.6  113.6 195.9  142.3 196.5  129.8 0.807 Starch(g) 524.4  291.1 541.3  290.7 552.7  336.4 648.7  342.2 0.206 Alcohol (g) 7.4  26.3 3.3  11.0 1.9  10.9 1.8  5.4 0.001 % E protein 16.0  4.0 15.6  4.9 14.9  4.7 13.7  3.4 0.004 % E Fat 25.0  6.9 23.3  7.7 21.0  8.1 24.4  6.8 0.001 % E CHO 54.8  9.8 57.5  11.1 60.2  10.8 58.4  9.0 0.001 Data are mean  SD. Significant difference between occupation groups at p<0.001 and p<0.05. % E – percent of total energy intake

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4.5.4 Lifestyle behaviour of study population by occupation

Details of the lifestyle behaviour of the study population by occupation are shown in Table 4.20.

Smoking and consumption of alcohol varied significantly among the occupation groups. Cigarette smoking was highest in the domestic participants (65%, p=0.004) as well as the percent who consumed alcohol (47.0%, p<0.001). The students had the least percent of smoking (3.1%) and consumption of alcohol (2.6%).

The use of traditional medicine were significantly (p<0.001) more common in the domestic participants (73.1%). The level of physical activity varied significantly. Based on 24 hr activity level, the highest score was in domestic participants (31.2  5.5) and the lowest in professional participants (28.8  3.4). With the active hours, labourers were the highest (13.0  6.8) and professionals (9.8  5.0) and students (9.8  8.0) were similar.

Table 4.20: Lifestyle behaviour of study population by occupation

Professional Labourer Domestic Students P n 200 74 629 35 Cigarette smoking (%) 18.3 13.0 65.6 3.1 0.004 Alcohol (%) 37.4 13.0 47.0 2.6 0.001 Traditional Medicine (%) 17.5 6.7 73.1 2.7 0.001 Physical Activity 28.2  3.4 30.6  5.3 31.2 5.5 29.3  6.1 0.001 Physical Activity 9.8  5.0 13.0  6.8 12.3  7.5 9.8  8.0 0.001 Data are means ± SD and %. 1Physical activity in 24 hours 2Physical activity in active working hours

4.6 Characteristics of study population by Religion

Religion is an important part of Tongan life and many activities, including health promotion, are centred on church activities. The four major congregations are the Free Weslyan Church of Tonga (FWC), Roman Catholic (RC), Later Day Saints (LDS) and Free Church of Tonga (FOT). The minor religions which were grouped under “others” (Section 4.1.4) are not considered in this section.

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4.6.1 Anthropometric characteristics of study population by religion

A summary of the anthropometric characteristics of study population by religion is shown in Table 4.21.

The FWC participants were significantly older (43.2 ± 14.0 years, p<0.001), heavier, (BMI: 32.8 ± 14.0, kg/m2, p=0.015) and had larger (waist circumference: 100.1 ± 13.2cm, p=0.047). The mean weight, percentage of body fat and waist to hip ratio were similar between religions.

FWC participants had the highest rates of having a family member with diabetes (46%).

Table 4.21 Anthropometric characteristics of study population by religion

FWC RC LDS FCOT P n 440 109 120 260 Age (years) 43.2 14.0 38.3  14.3 36.7  14.5 41.8  14.3 0.001 BMI (kg/m2) 32.8  6.1 31.8  6.3 30.9  5.6 31.9  6.1 0.015 Weight (kg) 93.9  17.4 92.3  18.8 90.4  18.3 92.5  17.6 0.250 WC (cm) 100.1  13.2 98.8  14.8 96.2  13.7 99.9  13.1 0.047 Waist hip ratio 0.87  0.08 0.86  0.09 0.85  0.07 0.88  0.08 0.093 Percent body fat (%) 34.8  11.3 34.3  11.9 31.9  10.4 32.3  11.5 0.056 FHx of diabetes (%) 45.9 9.7 9.0 25.9 0.132 Data are means ± SD and %. WC – waist circumference; FHx – family history of diabetes

4.6.2 Clinical and metabolic characteristics of study population by religion

Details of the clinical and metabolic characteristics of the study population by religion are shown in Table 4.22.

There were no significant differences in any of the parameters between religious groups except for minor differences in total cholesterol:HDL ratio.

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Table 4. 22: Clinical and metabolic characteristics of study population by religion

FWC RC LDS FOT P n 440 109 120 260 Systolic BP (mmHg) 130.2  18.6 127.4  21.8 125.7  18.1 130.5  20.3 0.113 Diastolic BP (mmHg) 80.3  10.6 80.5  13.9 78.6  10.4 81.4  11.3 0.199 Total chol (mmol/L) 5.04  1.1 4.9  1.2 4.9  1.1 5.1  1.1 0.095 HDL chol (mmol/L) 1.09  0.3 1.08  0.2 1.11  0.3 1.10  0.3 0.364 TG (mmol/L) 1.26  0.9 1.29  1.0 1.26  1.0 1.27  0.8 0.998 Calc. LDL (mmol/L) 3.4  0.9 3.2  1.0 3.3  1.0 3.4  1.0 0.061 Total Chol:HDL Ratio 4.9  1.4 4.7  1.4 4.6  1.3 4.8  1.4 0.035 Creatinine (mmol/L) 0.08  0.02 0.08  0.02 0.08  0.02 0.08  0.02 0.586 ACR (mg/mmol) 1.4  2.2 1.4  1.9 1.6  2.7 1.5  2.8 0.506 Data are means ± SD

4.6.3 Nutrient Intake of study population by religion

A summary of the nutrient intake of the study population by religion is shown in Table 4.23.

Overall, nutrient intake was similar across religions with only minor differences in percent energy from protein. Alcohol intake differed significantly being highest in Roman Catholic and Free Church of Tonga participants and lowest in Later Day Saints.

Table 4.23: Nutrient intake of study population by religion

FWC RC LDS FCOT P n 440 109 120 260 Energy (kc) 4721.1  2359.2 5070.6  2733.8 5257.6  2385.7 4914.40  2115.7 0.087 Protein(g) 176.4  101.5 183.6  93.8 195.7  118.4 172.2  84.4 0.088 Total (g) 117.4  70.1 126.4  70.9 137.0  89.9 119.4  71.4 0.072 SFA t(g) 47.8  28.6 51.5  27.7 55.2  35.8 49.5  29 0.148 MUFA (g) 41.3  27.4 44.2  28.1 48.9  35.6 41.5  28.7 0.059 PUFA (g) 13.5  8.8 14.9  9.6 15.9  12.2 13.3  9.2 0.038 Cholesterol(mg) 508.6  85.4 531.3  86.9 545.9  88.2 522.7  91.1 0.087 CHO(g) 728.9  407.9 783.1  507.4 802.3  374.6 772.3  352.5 0.202 Dietary Fibre(g) 65.3  32.3 67.7  41.6 70.9  28.9 70.0  30.9 0.245 Total Sugars(g) 203.4  164.3 213.4  183.1 229.8  165.2 187.8  109.5 0.077 Starch(g) 525.5  330.0 569.6  435.0 572.4  309.7 584.5  303.0 0.146 Alcohol (g) 2.8  14.3 5.7  16.6 0.7  5.3 5.0  22.1 0.026 Energy - Protein(%) 15.6  4.8 15.3  4.6 15.3  4.6 14.4  4.1 0.027 Energy - Fat(%) 22.3  7.8 22.8  7.8 22.9  8.1 21.5  8.1 0.399 Energy - CHO(%) 58.3  10.9 57.7  10.5 58.3  10.5 60.0  10.9 0.187 Data are means ± SD.

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4.6.4 Lifestyle Behaviour of study population by Religion

Details of the lifestyle behaviours of the study population by religion are shown on Table 4.24.

Rates of cigarette smoking and alcohol consumption were significantly higher in the FWC participants, of whom 48.2% smoked and 38% consumed alcohol. Fourteen percent of the RC participants smoked and 24% consumed alcohol. The lowest rates were in the LDS participants of whom 2% smoked and 5% consumed alcohol.

There were no significant differences in the level of physical activity if calculated in 24 hr activity (p=0.085) and on active working hours ( p=0.244).

Table 4.24: Lifestyle behaviours of study population by religion

FWC RC LDS FCOT P n 440 109 120 260 Cigarette smoking (%)1 48.2 14.2 2.8 30.9 0.001 Alcohol (%)1 38.0 24.0 5.4 30.2 0.001 Traditional Medicine (%) 66.4 61.5 55.0 65.0 0.065 Physical Activity2 30.3  5.3 29.7  4.6 30.4  4.3 31.1  5.9 0.085 Physical Activity 3 11.6  7.1 10.9  6.4 12.0  6.5 12.5  7.7 0.244 Data are means ± SD and %. 1 Comparison between religion groups 2 Physical activities in 24 hours, 3 Physical activities in the active hours only

4.7 Characteristics of study population by Glucose Tolerance

The diagnosis criteria for newly diagnosed diabetes and impaired glucose tolerance have been discussed in Chapter 3. Of the 1016 individuals, 10.3% were found to have new diabetes and 9.3% had impaired glucose tolerance (IGT).

4.7.1 Anthropometric characteristics of study population by glucose tolerance

Anthropometric characteristics of the study population who were found to have diabetes or IGT were compared with people with normal glucose tolerance (NGT) (Table 4.25).

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People with newly diagnosed diabetes (50.9 ± 11.8 years) and IGT (47.4 ± 12.6 years) were significantly older than people with NGT (39.4 ± 14.1 years). The mean BMI, weight, waist circumference and waist to hip ratio were significantly higher in people with newly diagnosed diabetes and IGT compared with NGT. The percentage of body fat was higher with newly diagnosed diabetes (37.2 ± 8.8 %) and IGT (35.6 ± 11.3 %) compared with NGT (33.1 ± 11.6 %). A family history of diabetes was significantly more common in people with newly diagnosed diabetes (44.8%) and IGT (35.1%) compared with NGT (26.4%).

Table 4.25: Anthropometric characteristics of study population by glucose tolerance.

Diagnosis Group NGT IGT Diabetes P n 817 94 105 Age (years) 39.4  14.1 47.4  12.6 50.9  11.8 0.001 Body Mass Index (kg/m2) 31.6  5.8 35.0  7.0 34.8  5.9 0.001 Weight (kg) 91.4  16.7 100.5  20.5 99.9  18.9 0.001 Waist circumference (cm) 97.8  12.5 105.8  16.0 107.6  11.9 0.001 Waist hip ratio 0.86  0.1 0.90  0.1 0.90  0.1 0.001 Percent body fat (%) 33.1  11.6 35.6  11.3 37.2  8.8 0.003 Family history of diabetes (%) 26.4 35.1 44.8 0.001 Data are means  SD and %. NGT – Normal Glucose Tolerance, IGT – Impaired Glucose Tolerance, Diabetes – newly diagnosed Diabetes.

4.7.2 Clinical and metabolic characteristics of study population by glucose tolerance

Details of the clinical and metabolic characteristics of the study population by glucose tolerance are shown on Table 4.26.

Blood pressure was highest in newly diagnosed diabetes followed by IGT then NGT. Mean systolic blood pressure in newly diagnosed diabetes was 142.9 ± 21.0 mmHg, in IGT was 134.6 ± 21.6 mmHg and 127.1 ± 17.7 mmHg in NGT. Diastolic blood pressure followed the same pattern being highest in newly diagnosed diabetes (87.0 ± 10.8 mmHg), then IGT (83.0 ± 11.9 mmHg) then NGT (79.4 ± 10.7 mmHg).

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The mean total cholesterol levels were significantly higher in newly diagnosed diabetes (5.3 ± 1.2 mmol/L) than IGT (5.0 ± 1.1 mmol/L) and NGT (5.0 ± 1.1 mmol/L). Mean triglycerides and total cholesterol to HDL ratio were significantly higher in diabetes, followed by IGT then NGT. The HDL cholesterol was significantly lower in diabetes (1.0 ± 0.2 mol/L) and IGT (1.0 ± 0.2 mmol/L) than in NGT (1.1 ± 0.3). Calculated LDL-cholesterol was similar in diabetes, IGT and the NGT (p=0.483).

Mean albumin/creatinine ratio levels were significantly higher in diabetes (2.4 ± 3.0 mg/mmol) and IGT (1.7 ± 2.8 mg/mmol) than NGT (1.3 ± 2.2 mg/mmol). Creatinine level were similar between the diagnostic groups and the NGT (p=0.225)

Table 4.26: Clinical and Metabolic Characteristics of study population by Glucose Tolerance

Diagnosis Group NGT IGT Diabetes P n 817 94 105 Systolic blood pressure (mmHg) 127.1  17.7 134.6  21.6 142.9  21.0 0.001 Diastolic blood pressure (mmHg) 79.4  10.7 83.0  11.9 87.0  10.8 0.001 Total cholesterol (mmol/L) 5.0  1.1 5.0  1.1 5.3  1.2 0.001 HDL cholesterol (mmol/L) 1.1  0.3 1.0  0.2 1.0  0.2 0.001 Triglycerides (mmol/L) 1.2  0.8 1.4  0.9 2.0  1.4 0.001 Calculated LDL (mmol/L) 3.4  0.9 3.4  1.0 3.5  1.0 0.483 Total Cholesterol:HDL Ratio 4.7  1.3 5.1  1.3 5.6  1.8 0.001 ACR (mg/mmol) 1.3  2.2 1.7  2.8 2.4  3.0 0.001 Creatinine (mmol/L) 0.09  0.02 0.09  0.02 0.09  0.02 0.225 Data are means  SD unless indicated. NGT – Normal Glucose Tolerance, IGT – Impaired Glucose Tolerance, Diabetes – newly diagnosed diabetes. Significant different between diagnosis group (IGT and Diabetes) and NGT

4.7.3 Nutrient intake of study population by glucose tolerance

Details of the nutrient intake of the study population by glucose tolerance are presented on Table 4.27.

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Unadjusted total energy intake was similar between the three groups. Protein intake was also similar but total fat intake was highest in the NGT group (124.3 ± 74.1g) compared with IGT (111.0 ± 65.5g) and newly diagnosed diabetes (107.1 ± 62.7g). SAF and MUFA intake were also highest in NGT but PUFA intake was not significantly different across groups (p=0.131). There were no significant differences between the diagnostic groups in other nutrient intake. Percent of energy intake did not differ between groups but the percent contribution of energy varied being highest in NGT, but CHO was lowest in NGT.

When the nutrient intakes was adjusted for age and sex, the NGT group consumed significantly more total energy, protein, total fats, SFA fat, MUFA, PUFA, cholesterol, total CHO, dietary fibre, total sugars, starch than the other two groups.

Table 4.27: Nutrient intake of study population by glucose tolerance

Diagnosis Group NGT IGT Diabetes P n 817 94 105 Energy (kc) 4900.8  2323.4 ** 4868.1  2424.5 4494.8  2016.8 0.236 Protein (g) 180.0  99.1 ** 169.3  84.7 163.8  86.6 0.188 Total Fat (g) 124.3  74.1** 111.0  65.5 107.1  62.7 0.025 SAF (g) 50.9  30.0** 45.6  26.9 43.7  26.4 0.022 MUFA (g) 43.7  29.4** 37.9  25.0 37.4  24.3 0.026 PUFA (g) 14.1  9.5** 13.0  9.2 12.4  8.0 0.131 Cholesterol (g) 533.5  363.4** 472.5  282.9 465.1  281.6 0.063 Carbohydrate (g) 752.6  398.5** 786.2  438.7 709.9  331.5 0.391 Dietary Fibre (g) 67.7  32.9** 69.3  33.7 62.9  25.8 0.299 Total Sugars (g) 201.33  149.5** 209.9  164.0 197.2  138.9 0.826 Starch (g) 551.2  332.6** 576.2  358.2 512.7  279.0 0.379 Alcohol (gm) 3.8  17.7** 2.6  10.3 1.8  7.4 0.435 E from Protein (%) 15.2  4.6 14.7  4.1 15.1  4.7 0.521 E from Fat (%) 22.7  8.1** 20.7  7.9 21.0  7.1 0.019 E from CHO (%) 58.2  11.0** 60.7  10.5 60.2  10.1 0.035 Data are means  SD and %. **Significant different between diagnosis groups (Diabetes and IGT) and NGT at p<0.001 when nutrient intake were adjusted for age and sex. NGT – Normal Glucose Tolerance, IGT – Impaired Glucose Tolerance, Diabetes – newly diagnosed diabetes E – energy

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4.7.4 Lifestyle behaviours of study population by glucose tolerance

Details of lifestyle behaviours of study population by glucose tolerance are shown on Table 4.28.

The rate of smoking was similar among the three groups. Although alcohol consumption was highest in the NGT, this difference was not significant (p=0.348). The use of traditional medicine was also similar the three groups.

People with newly diagnosed diabetes and IGT were less active than the NGT group. Mean 24 hour physical activity was slightly higher (p=0.004) in NGT (33.6 ± 6.8) than IGT (31.1 ± 5.1) and diabetes (30.4 ± 5.9). Activity level based on active hours was significantly (p<0.001) lower in newly diagnosed diabetes (9.7 ± 7.7) and IGT (11.4 ± 7.4) than NGT (14.3 ± 8.4).

Table 4.28: Lifestyle behaviour of study population by glucose tolerance

Diagnosis Group NGT IGT Diabetes P n 817 94 105 Cigarette smoking (%) 28.8 30.1 28.6 0.944 Alcohol (%) 13.6 12.8 8.6 0.348 Traditional Medicine (%) 61.9 68.1 67.6 0.301 Physical Activity1 33.6  6.8 31.1  5.1 30.4  5.9 0.004 Physical Activity2 14.3  8.4 11.4  7.4 9.7  7.7 0.001 Data are means  SD and %. 1Physical activity calculated base on 24 hours activity. 2 Physical activities calculated based on active hours only NGT – Normal Glucose Tolerance, IGT – Impaired Glucose Tolerance, Diabetes – newly diagnosed diabetes. Significant different between diagnosis group (Diabetes and IGT) and NGT

4.8 Prevalence of Overweight and Obesity.

The prevalence of obesity was assessed using a classification system for defining overweight and obesity in Pacific Island populations. This is based on the South Pacific Country (SPC) charts where two BMI units are added to the cut-offs used for Caucasians. These higher cut-offs are based on the assumption that Pacific Island

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people are more muscular than Caucasians. This has subsequently been supported by body composition data (Swinburn et al., 1996; Rush et al., 1997).

Using these ranges for Pacific people where overweight is defined as a BMI between 27.1 kg/m2–32 kg/m2, 30% of the population were overweight and 49% were obese (BMI>32 kg/m2). Two percent of the total study population was classified as underweight (BMI≤22.0 kg/m2) and 19% were within the healthy weight range (BMI 22.1–27.0 kg/m2).

4.8.1 Prevalence of overweight and obesity by age group

Details of the prevalence of overweight and obesity by age groups are shown in Table 4.29 and Figure 4.6.

Overweight and obesity increased significantly with age, up to ages 45-54 and then decreased significantly thereafter. Overweight was more prevalent (35%) in the 35 – 44 years age group, and obesity was highest (58%) in the 45-54 years age group. More than 70% of the age groups 25 -54 are either overweight or obese. Overweight and obesity was less prevalent in the young age groups 15 – 24 years old.

Table 4.29: Prevalence of overweight and obesity by age groups

Age groups Body Mass Index 22.0 22.127.0 27.132.0 32.0 P n (%) 20 (2.0) 191(18.8) 308(30.4) 495(48.8) 15-24 61.5 26.7 7.1 4.7 0.001 25-34 17.7 33.9 25.9 22.5 0.001 35-44 7.4 16.6 34.5 41.5 0.001 45-54 0 13.0 29.0 58.0 0.001 55-64 7.5 19.9 35.5 37.1 0.001 65+ 13.9 43.4 35.3 7.4 0.001 Data are means % unless otherwise indicated. P value for differences among groups.

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Figure 4.6: Prevalence of overweight and obesity by age group

Overweight Obesity 100 90 80 70 60 50 40

Prevalence (%) Prevalence 30 20 10 0 15 - 24 24 - 34 35 - 44 45 - 54 55 - 64 65+ Age Group (years)

4.8.2 Prevalence of overweight and obesity by location

Details of the prevalence of overweight and obesity by location is shown in Table 4.30 and Figure 4.7.

Overweight and obesity were very common in both Vava‟u /Ha‟api (83%) and in Tongatapu (79%). Overweight was more prevalence in Tongatapu (63%) while obesity was higher in Vava‟u/Ha‟apai (55%) participants.

Table 4.30: Prevalence of overweight and obesity by geographic location

Body Mass Index 22.0 22.127.0 27.132.0 32.0 p n 308 495 Ha‟apai & Vava‟u (%) 27.7 55.4 0.001 Tongatapu (%) 30.4 48.8 0.005 Data are %. P value for difference across BMI groups.

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Figure 4.7: Prevalence of overweight and obesity by location

50 Obese

Overweight Prevalence(%) 40

0 Ha’apai & Vava’u Tongatapu

4.8.3 Prevalence of Overweight and Obesity by Occupation

Details of prevalence of overweight and obesity by occupation are shown on Table 4.31.

Obesity was highest in the domestic participants (50.2%), followed by the professionals (49.5%) and labourers (47.3%) and lowest in the students (14.3%).

Overweight was highest in the students (40%) and lowest in the labourers (24.3%).

Table 4.31: Prevalence of overweight and obesity by occupation

Body Mass Index Total  22.0 22.127.0 27.132.0 32.0 p* n 14 179 290 455 Professional 1.0 15.0 34.5 49.5 0.001 Labourer 1.4 27.0 24.3 47.3 0.001 Domestic 1.1 18.6 30.0 50.2 0.001 Student 11.4 34.3 40.0 14.3 0.001 Numbers represent %. P value for comparison between groups.

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4.8.4 Prevalence of overweight and obesity by religion

Details of the prevalence of overweight and obesity by religion are shown in Table 4.32.

Overweight and obesity were highest in the FWC participants. Overweight was more prevalent in the FCT participants and obesity was highest in the FWC. More than 70% of the FWC, RC and LDS are either overweight or obese. Overweight and obesity was less prevalent in the FCT participants.

Table 4.32: Prevalence of overweight and obesity by religion

Body Mass Index

22.0 22.127.0 27.132.0 32.0 p* n 20 189 303 488 FWC 0.9 17.3 29.4 52.4 0.009 RC 5.6 18.5 28.7 47.2 0.009 LDS 4.2 25.8 25.0 45.0 0.009 FCT 20.0 28.0 30.4 22.7 0.009

4.9 Characteristics by Body Mass Index (BMI)

Body Mass Index (BMI) is commonly measure of weight used to assess the proportion of the population who are overweight or obese.

4.9.1 Anthropometric Characteristics by BMI

Details of the anthropometric characteristics of the study population by BMI are shown in Table 4.33.

There was a strong relationship between increasing age and increasing BMI (p<0.001). As expected weight, waist circumference, waist to hip ratio and percentage of body fat increased significantly with increasing BMI (p<0.001)

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Table 4.33: Anthropometric characteristics of study population by BMI

Body Mass Index(BMI) 22.0 22.127.0 27.132.0 32.0 P n (%) 20 (2) 191(18.8) 308 (30.4) 495 (48.8) Age (years) 28.5  15.9 39.2  17.0 40.9  14.9 42.8  12.1 0.001 Weight (kg) 62.6  6.3 74.5  8.1 86.6  9.1 105.6  14.4 0.001 Waist circumference (cm) 76.2  6.4 86.1  7.8 95.7  8.8 108.1  10.9 0.001 Waist hip ratio 0.8  0.05 0.8  0.07 0.9 ) 0.08 0.9  0.08 0.001 Percent body fat 18.5  9.0 22.8  9.6 29.5  9.1 41.0  7.7 0.001 Data are mean  SD. P values for comparisons between groups.

4.9.2 Clinical and metabolic characteristics by BMI

The details of the clinical characteristics of the study population by BMI are shown in Table 4.34.

Both systolic and diastolic blood pressure increased significantly with increasing BMI (p<0.001).

There was also a positive association between increasing BMI and lipids. The increase in total cholesterol was not significant (p=0.054). However HDL cholesterol significantly (p<0.001) decreased with increasing BMI while triglycerides, total cholesterol to HDL ratio increased significantly (p<0.001) with increasing BMI.

The mean creatinine level did not change with BMI. Albumin/creatinine ratio differed between groups with the highest levels in the underweight participants, then decreasing across the middle weight groups and increasing again in the heaviest group (p=0.021).

Participants who have family member with diabetes varied between the BMI level, with the highest prevalence in underweight (p=0.015).

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Table 4.34: Clinical and metabolic characteristics of study population by BMI

Body Mass Index 22.0 22.127.0 27.132.0 32.0 P n 20 191 308 495 SBP (mmHg) 116.0  11.4 124.0  9.6 128.8  19.4 132.4  18.9 0.001 DBP (mmHg) 73.2  9.7 76.4  10.3 79.2  10.2 83.1  11.1 0.001 Total cholesterol (mmol/L) 4.4  1.1 5.0  1.3 5.0  1.1 5.1  1.0 0.054 HDL cholesterol (mmol/L) 1.3  0.3 1.2  0.3 1.1  0.3 1.0  0.2 0.001 Triglycerides (mmol/L) 0.7  0.4 1.0  0.6 1.3  1.0 1.4  0.9 0.001 Calculated LDL (mmol/L) 2.8  1.0 3.3  1.1 3.4  1.0 3.4  0.9 0.026 Total Cholesterol:HDL Ratio 3.6  1.0 4.3  1.4 4.8  1.4 5.0  1.2 0.001 Creatinine (mmol/L) 0.08  0.02 0.08  0.02 0.08  0.02 0.08  0.02 0.547 ACR (mg/mmol) 2.4  6.3 1.3  1.8 1.2  1.8 1.6  2.6 0.021 Family hx of diabetes (%) 35.0 21.5 27.1 33.3 0.015 Data are means ± SD unless indicated. P value for comparison between groups. SBP – systolic blood pressure; DBP - diastolic blood pressure.

4.9.3 Nutrient intake by BMI

Details of the nutrient intake of the study population by BMI are presented in Table 4.35.

Total energy intake was similar across BMI groups. Protein, total fat, SFA, MUFA, PUFA, total CHO, dietary fibre, sugars and starch intakes were also similar. Alcohol intake decreased with increasing BMI. There was a significant variation in the contribution of protein to energy intake but the contribution of fat and CHO did not differ.

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Table 4.35 Nutrient intake of study population by BMI

Body Mass Index 22.0 22.127.0 27.132.0 32.0 P N 20 191 308 495 Energy (kc) 4907  2191.8 5084.5  2386.6 4914.6  2277.2 4732.3  2292.5 0.320 Protein(g) 188.7  85.1 177.7  95.5 176.2  95.0 177.4  98.8 0.956 Total (g) 135.6  73.8 125.4  76.9 121.4  73.3 119.2  70.3 0.613 SFA (g) 56.8  28.0 51.9  30.9 50.1  29.8 48.4  28.8 0.351 MUFA (g) 47.9  31.3 44.1  30.5 42.2  28.8 41.9  27.6 0.667 PUFA (g) 14.6  10.8 13.6  10.3 13.8  9.7 14.0  8.7 0.959 Cholesterol(mg) 574.8  280.8 519.8  335.9 523.3  359.4 517.0  352.0 0.908 CHO(g) 705.5  403.7 797.3  413.1 764.0  379.7 728.3  398.4 0.184 Dietary Fibre (g) 64.5  35.5 70.5  31.1 67.7  30.7 66.1  33.7 0.437 Total Sugars(g) 198.4  226.5 207.9  164.8 204.5  153.8 198.1  137.4 0.867 Starch(g) 507.1  321.2 589.3  314.2 559.5  314.2 530.1  334.2 0.165 Alcohol (g) 9.9  29.0 4.2  19.1 4.7  20.2 2.1  10.9 0.033 E. Protein (%) 16.0  3.7 14.4  4.1 15.0  4.5 15.5  4.8 0.043 E. Fat (%) 25.3  10.3 22.0  8.4 22.1  7.6 22.4  7.9 0.343 E. CHO (%) 54.1  12.4 59.6  10.9 58.8  10.6 58.4  10.9 0.161 Data are means ± SD. P value for differences among groups.

4.9.4 Lifestyle behaviour by BMI

Details of the lifestyle behaviours of the study population by BMI are shown in Table 4.36.

The rate of smoking and alcohol consumption decreased significantly with increasing BMI whereas the use of traditional medicine increased with increasing BMI. The level of physical activity was significantly lower in the overweight and obese participants, both over 24 hours and in active hours.

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Table 4.36: Lifestyle behaviour of study population by BMI

Body Mass Index 22.0 22.127.0 27.132.0 32.0 P n 20 191 308 495 Cigarette smoking (%) 40.0 41.1 34.7 19.4 0.001 Alcohol (%) 25.0 18.5 19.8 6.3 0.001 Traditional Medicine (%) 45.0 57.6 60.7 67.3 0.021 Physical Activity 32.1  4.4 31.8  6.4 31.0  6.0 29.4  4.0 0.001 Physical Activity2 14.1  4.7 12.8  8.1 12.0 7.9 11.1  5.9 0.020 Data are means % unless otherwise indicated. P value for differences among groups. 1Physical activity calculated base on 24 hours activities. 2 Physical activities calculated based on active hours only

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CHAPTER 5

5. DISCUSSION

5.1 The Study Population

One thousand and twenty four Tongans aged 15 years and older participated in this study. These subjects were randomly selected from the three main islands groups in the Kingdom of Tonga, Tongatapu (the main urban area) and Ha‟apai and Vava‟u (more rural area, and more traditional lifestyle) and these participants were reasonably representative of the general population living in Tonga.

The age and sex structure of the study participants is shown in Table 4.1 and Figure 1. Compared with the 1996 Census, the study had fewer young men and women in the 15– 24 year and 25–34 year age groups. On the other hand, women aged 35 years and over were over-represented in the study, as were men aged 55 years and over. These differences from the total population are likely to be accounted for by the older age structure of the non-paid employed people (domestic work) who were more available to take part in the survey. More women than men participated in the survey (57.6%) as men were less likely to be available. The sampling method involved selecting men and women 15 years and older from alternate households. However, if a person of the nominated sex was not available at the household and the survey team found a person of the opposite sex who was more willing to participate, we felt obligated to give them the opportunity to participate, provided that the other selection criteria were met. It is culturally inappropriate to turn down those who volunteered to take part. In addition, Tongan women are likely to be more health conscious and with their supportive role in the community, they were expected to take part, resulting in more women being selected. It is also more difficult to attract young people to participate in a survey about health issues that affect mainly older people. In addition the timing of the survey in Tongatapu (September–October) was during the school preparation time for examinations and students were hesitant to take time off school to participate in a

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survey that could take upto half a day. The survey times also impacted on those who were working regular daytime hours.

The majority of the study participants were aged between 25 and 54 years and therefore either had established or were establishing their own families and therefore the nutrition information gathered should be directly relevant for public health measures aimed at improving nutrition.

The geographical distribution of the study participants was similar to the general Tongan population. Sixty percent of the study population was from Tongatapu, compared with 68.5% of the Tongan population which resides on Tongatapu. Vava‟u and Ha‟apai is representative (25%) of the outer islands of Tonga.

The occupational status of the study participants was similar to the Tongan wider population, 1996 Census. The majority of the study population (67.1%) was engaged in labourer and domestic activities - either in agriculture (subsistence farming, working in the plantation), fishing, making handicrafts or house work, and a small proportion (3.7%) was made up of students (primary to tertiary level). In the 1996 Census, the un- employed population included 52% who were doing housework (domestic), with 54.4% of the employed population engaged in agriculture, fishing and making handicrafts (labourers).

Religion plays a major role in the lives of Tongans therefore it is an important variable in any study of Tongan characteristics. The Tongan population has been almost entirely Christian for more than 100 years and much of the culture is structured around Christian belief. Religious status of the study population was very similar to the religious status in the Tonga 1996 Census. Religion in this study was assessed in terms of which church the participant attended on a regular basis or with whom they could identify. The largest religious group was the Free Weslyan Church of Tonga (FWCT) which is still the main Christian denomination in Tonga. Other major religions included Roman Catholic, Latter Day Saints, the Free Church of Tonga and the Church of Tonga. Only 2 % of the study population was not associated with any religion.

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5.2 Nutrient Intake

5.2.1. Overview

Nutrient intake of study participants was assessed using a food frequency questionnaire, the first study in Tonga to use a food frequency questionnaire. It was designed to obtain qualitative, descriptive information about the usual intake of food and nutrients over the past year (as discussed in section 3.6.2.4.1).

Appropriateness of food intake was assessed by comparison with recommended dietary intake (RDI) to meet the nutritional needs of a healthy person. The purpose of RDIs is to recommend nutrient intakes to meet nutritional needs of the population with different age, gender, size and physiological status (Truswell et al;. 1983).

The RDIs of the Australia and the New Zealand nutrition guidelines were used for this comparison (Table 5.1). Both guidelines recommend a high carbohydrate (50–55%), moderate protein (10–15 %) and low fat (30%) diet. Target values for percentage energy contribution from protein, total fats, SFA, MUFA, PUFA and Carbohydrate, cholesterol and fibre are shown in Table 5.2.

Table 5.1: Comparison of the New Zealand Taskforce Target Values and the Australian Recommended Dietary Intakes (RDI)* with the Study Population Mean Intake

Male Survey Results Females Survey Results 19 – 64+ years 19 – 64 + years Energy (kcal) 2330 – 2550 5308 1900 - 1940 4522 Protein (g) 55 193 45 166 % E Protein 12 15 12 15 % E Carbohydrate 50 – 55 58 50 – 55 59

% E Total Fats 30 – 33 22 30 – 33 22

% E SAT Fats 8 – 12 12 8 – 12 10

% E MUFA 10 – 20 10 10 – 20 9

% E PUFA 6 -10 3 6 – 10 3

Cholesterol (mg) <300 573 < 300 482 Fibre (g) 25 – 30 71 25 – 30 65

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5.2.2 Total Calories

The mean (± SD) daily total energy intake of the study participants was 4855.8 ± 2304.4 kcal and males consumed significantly more than females (5308.4 ±2366.4 vs 4522.3 ± 2201.1 kcal, p=0.009). In comparison with RDIs, the survey results indicated that Tongans have a very high caloric diet, more than double the recommendation for both males and females participants. If the total energy intake is greater than the energy expended over a period of time, it is highly likely that obesity will develop in an otherwise healthy individual (Bray, 1996).

The mean total energy intake significantly decreased with increasing age with those aged 15-24 years having the highest energy intake (5472.0 ± 2336.5 kcal) and those aged 65 years and over having the lowest energy intake (4056.7 ± 1638.2 kcal). The total calorie intake was similar among occupation groups and between religious groups.

Although direct comparison with past studies is limited because of different survey methods, the study findings confirm the high caloric intake described in previous studies in Tonga. Langley studied (1952) reported an average daily calorie intake of 3200 kcal using a quantitative dietary survey collected over a 3 month period in 22 adults in Kolovai, a rural village in Tongatapu.

The nutrition survey by Adachi (1976) also found that calorie intake was generally high. A two day (Thursday and Friday) food record was collected from 22 adults (16 females and 6 males) in „Uiha, Ha‟apai. The finding shows that the energy intake was high with 6 of the females consuming over 3000 kcal and 4 of the males consuming over 4500 kcal.

The higher consumption of energy in the younger age groups is consistent with the findings of previous studies in Tonga and may be related to the consumption of imported food among the younger age groups (Finau et al., 1987; Engleberger, 1983).

The total calorie intake was similar among the occupation groups but professional participants consumed the highest percentage of energy from fats (25%) and protein

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(16%) while domestic participants had the highest percentage of energy from carbohydrate (60%). These differences are again consistent with differences related to the consumption of more imported and take away food by the younger age groups and more traditional foods by older domestic workers. Also dining out is a social function in the professional arena, which could contribute further to the higher protein and fat intakes in this group.

Overall, the nutrient intake was similar between the religious groups, with only small differences in energy contribution from protein and alcohol intake. Not surprisingly alcohol intake reflected congregation practices where alcohol is not restricted and is usually part of their social gathering. The low alcohol intake in the Latter Day Saints aligns with their fundamental beliefs including abstinence of alcohol. Though the Free Weslyan Church does not restrict alcohol intake, avoiding alcohol is promoted by the church.

5.2.3 Protein Intake

Protein contributed a mean (± SD) 15.2 ± 4.6% of energy with average daily protein intake being 177g (males 193.5g vs females 165.5g). Percentage of energy contributed by protein was similar between male and females participants (15%), slightly higher than the RDI of 12% of total energy.

The RDI for adults for protein is 55g for males and 45g for females. Compared with these guidelines, the current study indicated that the study population has a very high protein intake with the mean protein intake of males (193.5g) and females (165.5 g) being well in excess of the RDI for protein. Tongatapu participants‟ protein intake (199.1g) was higher than the Ha‟apai and Vava‟u participants (145.2g), both intakes being well in excess of the RDI for protein.

Previous studies have reported lower daily protein intakes. The study by Langley in 1952 (Engleberger, 1983) reported a protein intake of 69g per day. A great percentage of protein was from plant sources, including pumpkin, sweet potato, hibiscus (pele) and taro which were considered a substitute for meat. Adachi nutrition survey in 1976 as

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reported by Engleberger (1983) in „Uiha, Ha‟apai found that only 6 of the 22 participants had a protein intake over 100g daily, of which 60% was of animal origin.

Local protein foods include fish (most common), seafood, beef, chicken and pork, fruit bats and land crabs. Imported protein, which is more widely available, includes tinned fish, corned beef, mutton flaps, chicken (high fat cuts from America), poultry and other meat products and a range of other foods such as ham and luncheon. The current study indicated a very high protein intake compared with past surveys, and could indicate the increased availability of animal protein. However the food source of nutrients was not assessed in this study. A vegetarian diet is almost unknown in Tonga, and therefore, one could assume that the high protein intake would be mainly from animal origin, but this may vary between locations in Tonga. Finau et al. (1987) reported that urban people in Nuku‟alofa ate more imported foods such as mutton, chicken, beef, tinned fish and more meals with flour products than rural people in Foa. Rural people consumed more fresh fish and shellfish than did urban people. Nuku‟alofa people were consuming western- type foods whereas the Foa people were eating traditional foods. Similar findings were reported in the 1986 National Nutrition Survey in Tonga (Maclean et al., 1992). Consumption of imported foods was highest among urban adults and rural participants tended to consume more local produce of starchy roots or fruit crops, coconut cream at most meals, and fish on a daily basis.

The high percentage of protein in the Free Weslyan Church participants could be related to feasting in this church, which holds regular feasting throughout the year. The amount and types food provided claim to be a blessing in God‟s service. Blessed are those who give as they will be blessed abundantly. The cultural value and role of food play a major part in the church activities. Although the other churches hold feasts, they are not as regular as the Free Weslyan Church.

5.2.4 Carbohydrate Intake

Carbohydrate contributed a mean (± SD) 58.9 ± 10.9% of energy with average daily carbohydrate intake being 751g (males 819.1 ± 410.0 vs females 701.3 ± 378.1g).

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Vava‟u and Ha‟apai participants‟ carbohydrate intake was significantly higher than Tongatapu participants (62.3 ± 10.8 vs 56.2 ± 10.3%; p0.001).

The higher intake of carbohydrate in the older age groups suggested that traditional and local food are still more frequently consumed by older adults which is consistent with previous findings (Finau et al., 1987, Mclean et al., 1992).

This study showed that carbohydrates (CHO) are the main food items in the Tongan meal. Starch was the major contributor to the total CHO intake. The study population mean daily intakes were 550g for starch, 67g for dietary fibre and 202g for total sugar. The high starch component is a result of the dietary sources of starch in Tonga. The many stable foods of taro (Colasia esculenta), cassava (Manihot esculenta), yam (Dioscorea spp.) and breadfruit (Artocarpus communis) have a much higher starch content per 100g than potato or rice. For example, boiled taro and cassava contain 25.3g and 32g of starch per 100g of food compared with boiled rice and potato which contain 17.5g and 17.9g starch per 100g of food respectively (NZ Food Composition Tables, 2001).

In this study, the higher intake of carbohydrate in the Vava‟u and Ha‟apai participants is consistent with a previous study conducted in Tonga and reflects differences in food eaten. Finau et al. (1987) used the 24-hour recall method and reported that Nuku‟alofa (Tongatapu) people were consuming western-type foods whereas the Foa (Ha‟apai) people were eating traditional crops. Similar findings were reported in the 1986 National Nutrition Survey in Tonga which employed the 24 hour recall method. This study found that the differences in dietary patterns between urban and rural areas were attributable to availability of foods. Rural adults tended to consume more local produce (Maclean et al., 1992).

Englberger (1983), reported from a review of 13 nutrition surveys in Tonga, that rural- urban differences were probably due to a combination of factors such as greater availability of foods, an inconsistent supply of local foods or the lower cost and convenience and cooking of staples. For the Ha‟apai islands, the diet consisted predominantly of local starch roots or fruit crops, coconut cream at most meals, and fish which was usually eaten on a daily basis.

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The high daily sugar intake (202 g) also reflects the total amount of food eaten, especially with a high carbohydrate intake The studies by Finau et al. (1987) and Maclean et al. (1992) suggested that consumption of imported food (soft drinks, cakes, sugary food etc) was high, especially in urban area of Nuku‟alofa.

5.2.5 Dietary Fibre

The mean total dietary fibre intake of 67g is high - double the RDI of 25-30g dietary fibre per day. This is the result of the large daily carbohydrate intake. The staple food in Tonga is not extremely high in dietary fibre. Cassava, taro and breadfruits contribute 2.3g dietary fibre per 100g. In an average daily consumption of 4 servings of taro (400g) per day, it contributes only 9.2g dietary fibre per meal. Even if the Tongan population reduced total caloric intake by half, the recommended amount of daily dietary fibre intake for adults would still be met.

5.2.6 Fat Intake

Fat contributed a mean (± SD) 22.3 ± 8.0% of energy with average daily fat intake being 121g (males 131.2 ± 72.6 vs females 114.0 ± 71.6g). The mean total daily fat intake was higher in the Tongatapu participants than in Vava‟u and Ha‟apai participants (144.4 ± 75.0 vs 87.0 ± 52.3g, p0.001). Saturated (SFA) fat was the major contributor to the mean total daily fat intake.

This study indicated that even though the fat contribution to total daily energy is within the recommended allowance of < 30%, the total amount of fat consumed is high with the highest fat component being saturated fat, a recognized risk factor for cardiovascular disease. Different types of dietary fats have been shown to have different effects on risk factors and markers of cardiovascular disease (Grundy, 1986). SFA intake has been shown to correlate with blood cholesterol (Keys et al., 1986; Hu et al., 1997).

There has been an increasing consumption of imported high fat meats eg mutton flaps and turkey tails throughout the Kingdom of Tonga. The 1992 Nutrition Survey indicated that mutton flaps were the most frequently consumed meat (Foley et al., 1998). Thirty

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one percent of the study population consumed mutton on a daily basis and 27% consumed it three or more times a week. A higher proportion of urban than rural people ate chicken regularly.

None of the past national surveys or studies carried in Tonga assessed the percentage of energy from fats, or the types of fat (SFA, MUFA, PUFA). However, their findings indicated high consumption of imported high fat meat (mutton flaps, chicken, turkey tails). These foods are especially high in saturated fat.

The current study indicated a low intake of polyunsaturated fatty acids for both males (3.2%) and females (2.6%). This is consistent with a diet high in animal, rather than vegetables, sources of fat. Coconut is a staple food in the Tongan diet. Coconut differs from non-animal fat sources in that it is high in SFA with 91% of the fat being saturated. Though studies provide contradictory findings with regard to the effect of coconut oil on blood lipids (NZ Heart Foundation, 1999), the use of coconut cream in Tonga is a concern.

A popular Sunday meal is lu sipi (a parcel of taro leaves with mutton flaps and concentrate coconut cream). Traditionally, local meat – beef, chicken, fish or sea food made up the parcel. However, with the importation of mutton flaps, it has replaced the role of local meat, and therefore lu sipi become a modern tradition, as mutton flaps are not truly traditional. In Tongan culture, Sunday is literally considered the day of rest. It is a day when food is traditionally prepared in the morning, followed by church attendance, and then by a heavy lunch of traditional dishes, and siesta afterwards. In this respect, very little physical activity takes place on a Sunday, which disadvantages energy balance.

5.2.7 Alcohol

Overall, 13% of study participants consumed alcohol, and more men consumed alcohol compared with women (25.9 vs 3.6% , p0.001) and consumption was higher in Tongatapu (urban) than Vava‟u/Ha‟apai (rural) participants (18.4 vs 5.1%, p0.001). These results concur with the findings of an earlier study that alcohol consumption was higher in the urban area and also higher among males. Alcohol consumption in this

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study seems lower compared with Pacific Island people in other studies (Bathgate et al., 1994), although direct comparisons are limited by different study methodologies. In Tonga, alcohol, like cigarette smoking is much more likely to be consumed by males. The National Nutrition Survey in Tonga indicated that like smoking, the majority of drinkers began consuming alcohol in their teen years, with about one-tenth of both males and female drinkers beginning before the age 15 years (Foley et al., 1998).

Alcohol consumption was highest in the Free Weslyan Church participants (38%) and lowest in the Latter Day Saints church (5.4%). Not surprisingly alcohol intake reflected congregation practices where alcohol is not restricted and is usually part of their social gathering. The low alcohol intake in the Latter Day Saints aligns with their fundamental beliefs including abstinence of alcohol. Though the Free Weslyan Church does not restrict alcohol intake, avoiding alcohol is promoted by the church.

There is considerate evidence that moderate alcohol intake is associated with a reduced incidence of coronary heart disease (Kannel et al., 1996). However, excessive or „binge‟ drinking poses a number of health risks (Beaglehole et al., 1980).

In summary, this study shows that the nutrient composition of the Tongan diet meet the with current recommendations, but with excess total energy intake. This is a disadvantage for the Tongan population because of the current high prevalence of obesity. If the total energy intake is greater than the energy expended over a period of time, it is highly likely that obesity will develop in an otherwise healthy individual (Bray, 1996). Physical activity would need to be increased to compensate for this high calorie intake. However, with increasing modern technology in Tonga, especially the use of labour-saving appliances, the high caloric intake is likely to increase the obesity problem. Therefore, food and nutrition guidelines for Tonga should emphasise reducing the total amount of food consumed per day, which would not compromise the nutrient composition of the current food intake.

5.2.8 Physical Activity

In the current study, males reported more physical activity than females both if calculated over 24 hours or as active hours. This is consistent with the nature of

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domestic activities in Tonga. The most common, and undoubtedly the most intense of the physical activities was working in the plantation, or the bush. The combination of dry land and the sweltering heat adds to the intensity of slashing, digging, planting and the harvesting of food crops. It is because of this combination that bush work is generally regarded as a man‟s job. Most Tongan families engage in agriculture for their own produce, which is how they obtain their main staple foods to feed their family.

In this study, the level of physical activity was similar between Ha‟apai/Vava‟u and Tongatapu participants if calculated over 24 hours (30.3 ± 4.9 vs 30.5 ± 5.5, p=0.729) but slightly and significantly higher in Vava‟u/Ha‟apai participants if based on active working hours (12.4 ± 6.9 vs 11.3 ± 7.1, p < 0.05). This small difference is probably due to many Tongatapu residents, including professionals, maintaining a rural component to their lifestyle as they still engage in agricultural and subsistence farming and continue to work in the plantation after office work and on the weekends.

In this study, physical activity was similar across age groups when calculated as 24 hour activity. However, if calculated by active hours, it varied significantly (p=0.045) with age. The lowest level was in the 15–24 year age group and highest level in 55–64 year group. This age group was most likely to be engaged in some form of domestic work.

In Tonga, not everyday of the week is the same in terms of physical activity. Saturday tends to be the day when most activity takes place, whether at home doing housework, or working in the bush. A typical Saturday is considered a bush day, where people not only tend their plantation but also make preparations for the week ahead by harvesting crops, collecting firewood etc. Saturday is also the day to collect and prepare materials for Sunday‟s traditional food preparation.

Sunday is literally considered the day of rest for many Pacific Island cultures. It is a day when food is traditionally prepared in the morning, followed by church attendance, and then by a heavy lunch of traditional dishes, and a siesta afterwards. In this respect, very little physical activity takes place on a Sunday. Changing times have however brought about a few changes in terms of food preparation and lifestyle. For example, all families prepared food in the traditional oven but some use an electric oven, another time and

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labour-saving appliance. All in all, only very little light activity takes place on a Sunday.

The Tongan Nutrition Health Committee has adopted the international recommendation for at least 30 minutes of moderate activity on most days of the week which can bring about health benefits to people of all ages. In fact, by promoting a combination of activities that are already a part of one‟s everyday lifestyle, for example general housework, traditional craft making and working in the plantation, small contributions can be made towards an overall increase in levels of physical activity. In this way, time does not necessarily have to be set aside to achieve physical activity goals.

5.3 Prevalence of Overweight and Obesity

Obesity is a well recognized independent risk factor for many chronic diseases including cardiovascular disease, type 2 diabetes and other non-communicable diseases such as some cancers.

The WHO classification of obesity in adults for BMI may not be applicable to the Tongan population and higher cut-offs may be more appropriate for defining overweight and obesity in Pacific Island populations. The South Pacific Commission (SPC) has suggested two BMI units be added to the cut-offs recommended by the WHO (1997). These higher cut-offs are based on the assumption that Pacific Islands people are more muscular than Caucasians. This has subsequently been supported by body composition evidence (Swinburn et al., 1999).

Using the cut-off range suggested by SPC for Pacific people where overweight is defined as a BMI between 27.1–32 kg/m2, 30% of the study population was classified as overweight and 49% obese (BMI>32 kg/m2). This still shows a very high prevalence of overweight and obesity compared with 2% classified as underweight (BMI≤22.0 kg/m2) and 19% within the healthy weight range (BMI 22.1–27.0 kg/m2).

High rates of overweight and obesity have been documented in previous national surveys in the Tongan population. The 1986 Tongan National Nutrition Survey (Maclean et al, 1987) reported that the most prevalent diet-related problem in Tonga

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was overweight and obesity. About 78% of females were either overweight or obese, 39% had a BMI greater than 25 kg/m2 and 39% were obese (BMI30 kg/m2). Forty- eight per cent of men were either overweight or obese, and 10% were obese (BMI32 kg/m2).

Table 5.2 compares rates of overweight and obesity based on the BMI classification used in nutrition studies conducted in Tonga. Although there are some differences in the age range of the participants, the comparison illustrates the increasing prevalence of overweight and obesity in Tonga over the past 15 years. What stands out in this comparison (using the same BMI cut-offs) is the prevalence of obesity both in males and females. In the 1986 NCD survey, only 10% of the males were obese while in the 1992 National Survey, 29.8% of the males were obese, almost three times higher. In our study, 46.6% of the males were obese, indicating that among Tongan males obesity has increased four-fold since the 1986 Nutrition Survey.

Table 5.2: Comparison of prevalence of overweight and obesity according to the BMI classifications used in the 1986 National Nutrition Survey, the 1992 Non- communicable Disease Survey, and the current survey in Tonga

Females Males Overweight and Obese 1986 1992 1998-2000 1986 1992 1998-2000

N 1471 299 585 681 242 429

Oveweight1 38.8% 29.3% 22.6% 37.6% 35.7% 37.5%

Obese2 39.1% 54.8% 70.2% 10.0% 29.8% 46.6%

Overweight & Obese 77.9% 84.1% 92.8% 47.6% 65.5% 84.1%

1 BMI 25 - 29 kg/m2 for females and BMI 27.1 – 32 kg/m2 for males 2 BMI > 30 kg/m2 for females and BMI  32 kg/m2 for males

In the 1986 NCD Survey, 39.1% of the women were obese which increased to 54.8% in the 1992 National Survey. In our study, 70.2% of the females were obese. This indicates that the prevalence of obesity among the women has almost doubled over these survey periods. In addition, it is also important to note that overall, the prevalence of overweight has been steady for males and has decreased for females over the past surveys. However the total prevalence of overweight and obesity has increased to 92.8%

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in females and 84.1% in males using the BMI classifications used in the previous studies in Tonga. Therefore Tongan people are getting fatter.

This study found significant differences in BMI, percent of body fat and waist to hip ratio between males and females, but no significant differences in participants‟ weight or waist circumference. Male participants were significantly taller than females, which resulted in a lower BMI compared with females. Hip circumferences and mean percentage of body fat were significantly higher in females than in males while waist to hip ratio was lower in females because of similar waist circumference but larger hips in females compared with males.

Mean (± SD) weight for men and women was similar (male: 93.3 ± 17.4 kg and female: 93.1 ± 17.9 kg). Weight increased with age, from age 15-24 years to around 45–54 years and then decreased in the older age groups, for both males and females. The most significant increase in weight was in the younger age groups. From age 15–24 years to 25–34 year weight increased by 15.8 kg in females and 12.5 kg in males. In the 15–24 year age group, men were significantly heavier than women (female: 79.5 ± 12.8 kg, male: 82.6 ± 15.1 kg, p< 0.001) but this difference disappeared with increasing age.

These finding differ from previous studies in the Tongan population. Finau et al., (1983) studied 1605 women aged 15 to 49 years and 672 men aged 20–49 years, from urban Nukua‟alofa (Tongatapu) and rural Foa (Ha‟apai) and reported that the mean (± SD) weight was higher in males than in females, both in urban and rural areas. Males weighed 83.4 ± 0.4 kg in Nuku‟alofa and 75.2 ± 0.3 kg in Foa compared with females who weighed 76.3 ± 0.4 kg in Nuku‟alofa and 71.0 ± 0.4 kg in Foa Island.

Koike et al. (1984) also found that males were significantly heavier than females. They conducted a Medical and Nutrition study among two groups of Tongans from rural Uiha, Ha‟apai (n=108) and urban Kolofoou, Tongatapu (n=148) in people aged 30 years and older. The mean weight for all female age groups exceeded 80kg except for the age group above 70 years. Mean weight for males for all age groups exceed 85kg for rural males and close to 100kg for urban males.

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These differences are likely to represent true changes which have occurred over the 15 year period between the current and previous surveys. In 2004-5 a repeat Tonga NCD and Nutrition survey was carried out using an identical protocol and surveying the same sites as in the 1998-2000 survey. The 2004-5 survey again showed no difference in weight among men and women (S.Colagiuri, personal communication).

Recent research has highlighted the importance of genetic factors in determining individual susceptibility to obesity (Hill, 1998). However the sample in this study was homogeneous with 100 percent of participants being Tongan, so large genetic differences are unlikely. Therefore, the main factor in this increase is likely to be related to the environment, which promotes behaviours that cause obesity (Swinburn et al., 1999).

In this study, we did not find any association between current dietary fat and total calories with BMI, but BMI was related to physical activity. Overweight and obese participants had significantly lower levels of physical activity compared with normal and underweight participants.

The gender difference findings with regard to BMI in Tongans is consistent with the findings from other studies where the prevalence of obesity is higher among women than men (Bell et al., 2001), based on the same BMI cut-off for Pacific populations. For example, the prevalence of obesity in the Pacific Island population resident in New Zealand was 26% for males and 47.2% for females (Russell et al, 1999). In Samoa obesity prevalence was 48% for men and 70% for women in studies conducted since 1990 (Hodge et al., 1996), indicating that Samoans have the highest prevalence of obesity of any population in the world, higher than Native Hawaiians (Wahi et al., 1997; Dai et al.,2007) and Pima Indians (Losacker, 1992), in spite of the criteria for defining obesity being slightly different in each study. Obesity prevalence, standardised to Segi‟s world population was 58% for Samoan men and 77% for Samoan women living in urban Western Samoan (McGarvey, 1991; Collins et al., 1994)

However our study showed that the Tongan adult population now has a similarly very high prevalence of obesity (BMI ≥ 32 kg/m2 - 63% in men and 78% in women). If obesity is based on the BMI classification that were used in some previous studies in the

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Pacific population, then the total prevalence of combined overweight and obesity were 92.8% for Tongan women and 84.1% for Tongan men. This is higher than the prevalence rate of 50% to 75% in the Pacific communities, as reported by Coyne et al. (2000). A study by Schaaf et al (2000) observed no significant differences in BMI between Cook Islanders, Samoans, Tongans and Niueans. However, Bell et al (2001) found that Tongan men and women were bigger than their counterparts from other islands.

Apart from total weight, body composition is also an important risk factor for NCD. Studies have shown that central or abdominal obesity has a higher association with increased health risks (Larsson et al., 1984; Lapidus et al., 1984; Ohlson et al., 1985). Haffner et al. (1987) found that abdominal obesity is a better marker of metabolic and cardiovascular risk factors in women than in men. Waist and hip circumference can be used to measure different aspects of body composition and fat distribution and have independent and often opposite effects in determining risk for cardiovascular diseases (Seidell et al., 2001). Studies in two Pacific populations showed that increased waist to hip ratio was associated with glucose intolerance (Collins et al., 1994; Hodge et al., 1993). A waist circumference of greater than 102 cm in men and 88 cm in women is a risk factor for insulin resistance, diabetes mellitus and cardiovascular disease (WHO, 1997).

Findings in this study indicate that waist circumference and waist to hip ratio were significantly associated with increasing BMI. Overall, there was no significant difference in waist circumference (mean ± SD) for males (99.8 ± 13.3 cm) and females (99.2 ± 13.4 cm). However, mean (± SD) waist to hip ratio was significant higher in males (0.90 ± 0.08) than in females (0.84 ± 0.1, p< 0.001). This difference in waist to hip ratio reflects anatomical differences between men and women. In this study, women had significantly bigger hip circumferences than men (118.9 ± 12.8 cm vs 109.4 ± 9.2 cm, p< 0.001). The previous nutrition and health study in Tonga did not include waist and hip measurements, thus comparison of this result with previous findings was not possible.

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The present study showed some minor differences in the prevalence of overweight and obesity between urban Tongatapu and the more rural areas of Vava‟u and Ha‟apai. In total, 79% of participant from Tongatapu were either overweight or obese compared with 83% of those from Vava‟u/Ha‟apai. Overweight problems were significantly more prevalent in Tongatapu (30.4 vs 27.7% p = 0.005) while obesity was significantly higher in the Vava‟u and Ha‟apai participants (56.4 vs 48.8%, p=0.001). This finding is similar to the Tonga Nutrition Survey in 1986 (Maclean et al., 1987) which also found little difference in mean BMI of rural and urban Tongans. Therefore in Tonga there is little difference between urban and rural areas.

Age differences in these locations may have contributed to this finding. It has been previously demonstrated that as age increases so does BMI (Russell et al., 1999) and the Vava‟u and Ha‟apai participants were older than those from Tongatapu. Overall, in this study, the prevalence of obesity increased steeply from 17% to 61% between 15 and 35 year old age groups and then leveled out in the older age groups, decreasing to 38% in the 65+ year age group as demonstrated in Chapter 4. This is consistent with the1992 NCD and nutrition survey which included 940 Tongan adults (Foley et al., 1998). The rates of overweight (BMI 25-29.9 kg/m2) increased dramatically with age in females to over 90% in the middle-age (30-39 years) and for men rates of obesity were over 30% in the middle-age years There was a trend of increasing overweight and obesity with increasing age up to about 50 years when the level of obesity and overweight declines.

The mean age in the Vava‟u and Ha‟apai participants was 44.2 ± 13.1 compared with 39.6 ± 14.7 in those from Tongatapu and the age distribution was similar. These small differences are unlikely to have made a big contribution to the lack of difference in obesity rates between these two locations.

5.4 Nutrient intake and glucose tolerance

The study found a high prevalence of type 2 diabetes with an age- and sex- standardized prevalence of 15.1%. There was no gender difference in the prevalence of diabetes. Among those with diabetes, more than 80% had previously undiagnosed type 2 diabetes. Compared with the last survey in 1973, there has been a doubling in diabetes prevalence in Tonga.

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Prevalent diabetes was significantly associated with increasing age, BMI, weight, waist to hip ratio, percentage of body fat, and positive history of diabetes. In addition, low HDL-cholesterol, increased level of high blood pressure, total cholesterol, triglycerides, total cholesterol to HDL-cholesterol ratio, albumin/creatinine ratio and creatinine were also associated with prevalent diabetes.

Overall energy intake was similar between people with newly diagnosed diabetes, impaired glucose tolerance and normal glucose tolerance. There were minor differences in percentage of energy from fat and carbohydrate but no consistent pattern emerged. Even after adjusting for age and sex, no clear differences in pattern of energy intake was seen.

The lack of relation between macronutrients intake and glucose tolerance is not surprising given the cross sectional nature of this analysis. Prospectively collected data are more likely to show a relationship between food intake and the development of diabetes. People with impaired glucose tolerance and diabetes were significantly heavier than people with normal glucose tolerance and energy intake and reduced physical activities which contributed to this state in the preceding years is difficult to identify in a cross sectional study.

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CHAPTER 6

6. SUMMARY

This is the largest cross-section population-based epidemiological study in Tonga which collected dietary data and assessed metabolic status such as weight, glucose tolerance, lipids and hypertension.

This study showed a very high daily calorie intake, which is not surprising given the high prevalence of overweight and obesity in Tonga. Men consumed more than women and energy intake decreased with age. There were no significant differences among the occupation groups or between religions.

However the macronutrient composition of the diet is consistent with the recommended diet of high carbohydrate, moderate protein and low fat. Although the diet is influenced by western foods, there is a significant contribution from traditional foods, especially in the older age groups and in rural areas.

Carbohydrates are the main food items in the Tongan meal with starch the major component of carbohydrate intake, consistent with a high consumption of traditional foods. The diet also has a very high fibre intake, double the recommended daily intake of 30–40 g/day.

Protein intake is very high, nearly four times the RDI for both genders. Total fat intake is also high but as a percent of total energy intake is within the recommended amount of <30%. The major fat in the diet is SFA. Gender differences indicated that men consumed more SFA than women. The low intake of polyunsaturated fatty acids is consistent with a diet high in animal (mainly poor quality animal foods such as high saturated fat mutton flaps), rather than good sources of PUFA - vegetables sources and fish

However as stated earlier, one of the limitation of this study is that the sources of macronutrients were not obtained and therefore cannot be conclusive to say that the high saturated fat and protein intake are related to the poor quality of animal protein. In addition, none of the past nutrition survey in Tonga had used FFQ, nor a cross-sectional study. Therefore, further analysis of the survey data would allow evaluation of the

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nutrition quality of Tongan diets, and to facilitate comparison with traditional eating patterns.

Lifestyle behaviours between different religions were also observed. The rate of alcohol consumption and smoking was related to differences in religious fundamental beliefs.

Men, as expected were physically more active than women, and physical activity level was associated with weight. There was no urban-rural difference in level of physical activity consistent with urban men continuing to engage in agricultural and subsistence farming, and working in the plantation after office work and on the weekends.

The study showed a high prevalence of overweight and obesity. Using the WHO classification for BMI in adults, 60.4% of the study population was obese and 28.8% were overweight. If the BMI classification is based on the revised cut-off for Pacific Island populations, 49% were obese and 30% were overweight, and both were significantly higher in women than men. Therefore this study confirmed the high prevalence of obesity and overweight documented in previous studies in Tonga.

Using the same BMI classification used in previous studies in Tonga, the prevalence of obesity among Tongan men has increased at least four-fold and almost doubled among women over the past 12 years. Prevalence of obesity is increasing with age and is more of a problem in women than with men, and is seen in both rural and urban areas. Although larger body sizes may be viewed as acceptable and often desirable, Tongan people need to reconcile cultural belief about being big and obvious ill-health consequences of being overweight or obese, which is more prevalent today due to the modern lifestyle.

Overall energy intake was similar between people with newly diagnosed diabetes, impaired glucose tolerance and normal glucose tolerance. The lack of relation between macronutrients intake and glucose tolerance probably reflects the cross-sectional nature of this analysis.

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CHAPTER 7

7. STUDY LIMITATIONS

The cross-sectional nature of the study is suitable for identifying associations but does not allow any conclusions about causality. The other main limitation was that the study relied on self-reported dietary and physical activity information and an interpretation of these data.

A food frequency questionnaire was used to collect dietary data. Although this document assumes that a FFQ is appropriate for use in this cross sectional national survey, it is important to be aware of the strengths and limitations of the method. No dietary method can measure dietary intake without error (Cade et al., 2002). Errors could be made in the response to the few first questions, while the participants was getting used to the format of the questionnaire. Additionally towards the end of the questionnaire, the accuracy of responses may be decline as the participant could be bored and fatigue from a long questionnaire. The questionnaire was adapted from one used in a non-Tongan population but had Tongan foods added. Information obtained using such questionnaires is dependent on the participant‟s recollection of food eaten and frequency and is subject to under or over-reporting.

Obtaining accurate reports of foods eaten both alone and in mixed dishes is particularly problematic (e.g. vegetables as a whole portion or in a mixed dish). Asking separate question and increasing number of items in the food lists can lead to overestimation of intake (Krebs-Smith et al., 1995). A few foods (staple) were consumed more than once a day which led to gross overestimates for some people. Portion sizes used reflected the consumption patterns in the study population. However, there is a potential for overestimation, as subjects with the same frequency of consumption but different portion sizes, need to be adequately distinguished.

There is evidence that obese participants as a group under-report their food intake (Heitman, 1993), and some groups have found under-reporting of half of total energy intake (Prentice et al., 1986; Lichtman et al., 1992 ). However under-reporting would

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make the findings of excessive caloric intake observed in this study even more significant. One study found that reported dietary behaviour depends on whether particular foods are perceived as socially desirable or personally relevant (Worsley et al., 1984). This could lead to inaccuracies in reported food intake and could be a factor in reporting by Tongan people for whom food plays an important cultural role.

Cross sectional studies investigate relationships at a single point in time and, as such are unable to generate information on causality. As the study aims to compare different subgroups of the population, for example the effect of age groups, gender, occupation types and location, then the FFQ should be validated. Validation should have been done to assess whether the questionnaire agrees with a „gold standard‟ or other methods of assessing nutrient intake. As even subtle changes or modified version of the validated FFQ (Quigley et al., 1997), it could perform differently in different demographic groups and cultures. The validation is appropriate as incorrect information may lead to false associations between nutrient intake (macro-nutrients) and diseases related burden.

There were some inherent limitations in collecting physical activity data, especially when estimating the contribution from strenuous and not so strenuous activity. Participants who reported working in the plantation were assumed to work in the bush throughout the day, especially if they reported going to the bush for the whole day. In reality, some people could be working vigorously for a few hours and then resting or continuing with a low to moderate activity in the plantation. In addition, the women could be underestimating their level of activity. Household chores are women‟s duty in Tonga. These include sweeping the house, making beds, washing dishes/clothes, sweeping/picking up rubbish and fallen leaves around the home. Women tended to do less intense activity but for longer periods, whilst the men spent shorter time on more intense activities. In addition it was difficult to decide if walking to the shops, to church, or to visit relatives and friends could be defined as moderate activity. These walks were probably at a slower pace as people often carry heavy items. House-work was considered as a moderate activity, though the participants may have spent long hours in preparing food, washing and doing the house work.

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APPENDICES

Appendix I:

Survey Questionnaire

Appendix 1: Survey Questionnaire ID TONGA DIABETES SURVEY – REGISTRATION FORM

Name: Surname First Name

Address: 4 5 House/Unit no Street Name

Town

Date of Birth: Sex: Male Female Religion:

Family History Diabetes: Yes No Don‟t know If yes  Mother Father Siblings: Children:

History of Heart Disease: Heart Attack: Yes No Surgery: Yes No

Smoking: Current Past Neither  Cigarettes/day: Alcohol: Current Past Neither  gm/day Exercise: Yes No

Traditional Medicine: Yes No If yes  Nonu Other times per day/week/month If Other, specify: Duration:  6 month  6 month

Height: . cm Weight: . kg BMI: . Waist: . cm Hip: . cm W/H Ratio: .

Blood / mmHg BP Treatment: Yes No

Pressure: Tests Done Results Fingerprick Blood 5.3.2 5.3.2.3 . mmol/L If  6.0 and  11.0  Do GTT Red Glucose:  6.0 or  11.0  No GTT5.3.2.3.1.1 Green . HbA1c: % 5.3.2.3.1.2

Blood Glucose: . mmol/L Insulin: .

Creatinine: mol/L

Micro Albumin: . ratio Lipids: Cholesterol: . mmol/L HDL: . mmol/L Triglycerides: . mmol/L Antibodies: LpL markers:

Glucose Tolerance Test Blood Glucose: . mmol/L . mmol/L

(GTT): Insulin . . Time of Glucose drink: . am/pm

Other Assessments: Impedance: Nutrition Survey: ECG: Physical Activity Survey:

Health Promotion Survey:

Appendix II:

Food Frequency Questionnaire

Appendix II: Food Frequency Questionnaire Name: ______

TONGA DIABETES SURVEY

Food Intake Questionnaire

This is how to answer:

We are going to ask you “About how often did you usually eat these foods?” Use the following simple code to write your answer in the space next to each food.

If you NEVER had a food ______write N If you RARELY had a food ______write R

If you usually ate a food

About once a MONTH ______write 1M About twice a MONTH ______write 2M About three times a MONTH ______write 3M

About once a WEEK ______write 1W About twice a WEEK ______write 2W About three times a WEEK______write 3W and so on ______(4W, 5W, 6W etc)

About once a DAY ______write 1D About twice a DAY ______write 2D and so on ______(3D, 4D, 5D, etc)

We realise that some people have an exact idea of how often they ate particular foods, while others only have an approximate idea. Be as accurate as you can but don‟t spend too much time choosing your answers.

PLEASE GIVE AN ANSWER FOR EVERY FOOD

Here are some examples:

If you usually had:

Roast lamb about once a week write Roast Lamb ______

Boiled potatoes almost every day write Boiled potato ______(say 5 times a week)

A cup of coffee twice a day write Coffee ______

Kiwi fruit a couple of times a year write Kiwi fruit ______(ie: rarely)

How to answer: Times per Times per Times per Amount Never Rarely month week day 1 1 1 5.3.3 N R 2 M 2 W 2 D 3 3 3 and so on and so on

Q1. About how often did you usually eat these TAKEAWAY FOODS? (over the last 3 months)

Hamburger ______Fried Chicken ______Pizza ______Chinese food ______Fried fish ______Chip, potato or french fries ______

Q2. About how often did you usually eat these foods? (over the last 3 months)

Fruit (raw, cooked or frozen):

Fresh apple/pear ______Fresh citrus (eg orange, mandarin or grapefruit) ______Fresh banana ______Fresh melon (eg water melon) ______Fresh stone fruit (eg apricot, plum, peach) ______Fresh Kiwi fruit ______Fresh Pineapple ______Fresh Mango, pawpaw or breadfruit ______Fresh grapes ______Tinned fruit - with sugar ______Tinned fruit - without sugar (eg: Diabetic)______Stewed fruit ______Dried fruit ______Fresh piantonis ______Fresh tava ______Fresh Guava ______

Please name any other fruit eaten regularly

______

How to answer:

Times per Times per Times per Amount Never Rarely month week day 1 1 1 N R 2 M 2 W 2 D 3 3 3 and so on and so on

Q3. About how often did you usually have these drinks? (over the last 3 months)

Drinks: Glass of Milk ______Milkshake or thickshake ______Glass of cordial ______Glass of cordial Glass of powered fruit drink (eg: Raro) ______Glass of sweetened fruit juice (eg: Fresh-up) ______Glass of pure fruit juice ______Glass of fizzy drink (eg Coke, Fanta) ______Glass of low-cal drink (eg Diet Coke) ______Cup of tea ______Cup of coffee ______Cup of coffee substitute (eg Inka) ______Cup of Milo, cocoa or chocolate ______Glass of wine ______Glass of sherry ______Glass of port ______Serve of spirits (eg whisky) ______Large bottle or jug of beer ______Can or stubbie of beer ______Can or stubbie of low alcohol beer ______Glass of water ______Cup of maengalo (Lemon Grass) ______Cup of orange/citrus leaves ______

Please name any other drinks not listed above

______

Q4. Did you take milk: (circle ONE number in each line) Yes No Don’t drink it In your tea? 1 2 3 In your coffee? 1 2 3 In coffee substitute 1 2 3

Q5. Did you make your Milo, cocoa or chocolate drinks with:

1. Mostly milk? 2. Mostly water? 3. About half and half? 4. I didn‟t have Milo, cocoa or chocolate drinks?

Q6. When drinking milk or adding it to tea or coffee etc, which of the following did you usually use? (Circle ONE number).

1. Homogenized (blue top) 2. Whole milk (silver top) 3. Trim milk (green top) 4. Other (please specify) ______5. Longlife 6. Nestle (canned/condensed milk) 7. I didn‟t drink milk, or add it to tea, coffee or breakfast cereal

Q7. How many teaspoons of sugar did you usually take in the following? (If you didn’t use sugar write 0). Brown/Raw/White?

Tea ______teaspoons Coffee ______teaspoons Coffee substitute ______teaspoons Milo, cocoa or chocolate______teaspoons Cordial______teaspoons Fresh lemon drink______teaspoons

How to answer:

Times per Times per Times per Amount Never Rarely month week day 1 1 1 N R 2 M 2 W 2 D 3 3 3 and so on and so on

Q8. About how often did you usually eat these foods? (over the last 3 months) Meats and fish: Meat pie ______Bacon ______Hamburger (home cooked) ______Steak ______Mince dishes (eg mince, lasagne, bolognaise) ______Weiner schnitzel ______Pork chops ______Lamb or mutton chops ______Roast pork ______Roast beef ______Roast Lamb ______Fried or roast chicken (home cooked) ______Boiled or steamed chicken ______Sausages (eg: pork, beef, saveloys) ______Stew/casserole ______Brisket ______Mutton flaps ______Povi masima ______Tinned corned been ______Cold meat (eg: ham, salami) ______Organ meats (eg: liver, kidney) ______Pate ______Fished boiled, steamed or grilled ______Fish battered, fried (home cooked) ______Raw fish ______Tinned fish (eg: tuna, sardines, salmon) ______Shellfish (eg: pipis, mussels, oysters) ______Gravy ______Cheese sauce ______Tomato sauce ______Hot dog ______Sausage roll ______

Please name any other meat dishes not listed above

______

Q9. Which type of gravy did you usually use? (Circle ONE number)

1. Packet 2. Home made with dripping, lard or butter 3. Home made with vegetable oils or margarine 4. I didn‟t use gravy 5. I don‟t know

Q10. How many of the following did you usually eat at a time? (If you didn’t eat the food, write 0) 1. Meat pies (or portions of family meat pie) ______2. Rashers of bacon ______

3. Pork chops ______4. Lamb or mutton chops ______5. Sausages ______

Q11. When you ate meat with fat on it, did you eat (Circle ONE number)

1. All of the fat? 2. Most of the fat? 3. Some of the fat? 4. Little or none of the fat? 5. I did not eat meat

Q12. Which of the following was the most usual method of cooking meat in your household? (Circle ONE number)

1. Boiled in water 2. Microwave 3. Baked or casseroled 4. Fried or roasted 5. I didn‟t eat meat 6. I don‟t know 7. BBQ/grilled

How to answer:

Times per Times per Times per Amount Never Rarely month week day 1 1 1 N R 2 M 2 W 2 D 3 3 3 and so on and so on

Q13. About how often did you usually eat these foods? (over the last 3 months)

Vegetable servings (raw, cooked or frozen): Tomato ______Lettuce or celery ______Cabbage, brussel sprouts or broccoli ______Silverbeet or spinach ______Carrots ______Cauliflower ______Avocado ______Capsicum (green pepper) ______Onion ______Asparagus ______Green beans ______Green peas ______Cucumber, courgette or marrow ______Mushrooms ______Sweeetcorn ______Puha or watercress ______Kumara ______Pumpkin ______Boiled or mashed potato ______Roast or baked potato ______Chip potato (home cooked) ______Beetroot (fresh, tinned) ______Parsnip or swede ______Yam or taro tuber ______Taro leaf (eg: Palusami) ______Bean sprouts ______Coconut cream ______Green banana ______Pele leaves ______Cassava ______Giant Taro (Kope) ______Bread fruit (mei) ______Green Plaintain ______

Please name any other vegetables eaten not listed above

______

Q14. Which of the following was the most usual method of cooking vegetables in your household? (Circle ONE number)

1. Steamed or boiled in water 2. Microwaved 3. Baked or casseroled 4. Fried or roasted 5. I mainly ate raw vegetables 6. Hot Pot 7. I don‟t know

Q15. Which one of the following was usually used to fry your meat and vegetables (Circle ONE number)

1. Butter 2. Margarine 3. Lard or dripping (eg: chefade) 4. Vegetable oils (eg: safflower, corn) 5. “Dry-fry” - didn‟t add fat or oil 6. Animal fat (pork) - home made 7. I didn‟t eat fried meat and vegetables 8. I don‟t know

Q16. Which one of the following was usually used to roast your meat and vegetables (Circle ONE number)

1. Butter 2. Margarine 3. Lard or dripping (eg: chefade) 4. Vegetable oils (eg: safflower, corn) 5. “Dry-roast” - didn‟t add fat or oil 6. Animal fat (pork) - home made 7. I didn‟t eat fried meat and vegetables 8. I don‟t know

Q17. Did you add butter or margarine to your vegetables at the table? (circle ONE number)

1. No, rarely or never 2. Yes, sometimes 3. Yes, usually

Q18. Did you ad salt to your meals at the table? (Circle ONE number)

1. No, rarely or never 2. Yes, sometimes 3. Yes, usually

How to answer:

Times per Times per Times per Amount Never Rarely month week day 1 1 1 N R 2 M 2 W 2 D 3 3 3 and so on and so on

Q19. About how often did you usually eat these foods? (over the last 3 months)

Cereals, spreads, beans: Breakfast cereal ______Bran ______Plain biscuits (eg: Arrowroot) ______Fancy biscuits ______Crumpets ______Cabin bread ______Crispbread or crackers ______Pancake ______Doughboy (Maori dumpling) ______Maori bread ______Peanut butter ______Vegemite or marmite ______Honey, jam or marmalade ______Mayonnaise or salad dressing ______Fried rice ______Boiled rice ______Chinese food (home cooked) ______Pizza (home cooked) ______Pasta (eg spaghetti,macaroni, noodles ______Baked beans ______Other beans (eg. Soya, lima) ______Split peas or lentils ______Creamed soup ______Other soup ______Tongan Dumpling ______Manioke Tarro (cassava) ______To‟okutu (flour products) ______

Please name any other cereals dishes eaten not listed above

______

Q20. How many slices of these breads did you usually eat? If you did not eat the bread write 0. If you fill in “slices per day” don’t fill in “slices per week” as well)

White bread ______slices/day OR ______slices/week Brown bread ______slices/day OR ______slices/week Wholemeal bread ______slices/day OR ______slices/week Mixed grain bread ______slices/day OR ______slices/week Other bread ______slices/day OR ______slices/week Please describe ______

Q21. Which of the following did you usually spread on bread or crackers? (Circle ONE number)

1. Butter 2. Margarine 3. Butter or margarine equally as often 4. Neither

Q22. If you ate breakfast cereal, please answer this question. (If NOT, go to question 23)

a) What type of breakfast cereal have you been eating in the last three months. Specify the ONE most common______b) How many teaspoons of sugar or honey did you usually add to breakfast cereal? (Circle ONE number

0 ½ 1 1½ 2 2½ 3 c) How many teaspoons of sugar or honey did you usually add to breakfast cereal? (Circle ONE number). Teaspoons: 0 1 2 3 4 5 6 (1 dessertspoon = 2 teaspoons)

Q23. If you ate eggs, how many did you usually have? (eg: boiled, scrambled, fried or in omelettes; not in cakes etc). If you did not eat eggs write 0. ______eggs per day OR ______eggs per week OR ______eggs per month.

How to answer:

Times per Times per Times per Amount Never Rarely month week day 1 1 1 N R 2 M 2 W 2 D 3 3 3 and so on and so on

Q24. About how often did you usually eat these foods? (Over the last 3 months)

Dairy foods, sweets, snacks: Cheese ______Cottage cheese______Cream cheese or cheese spread ______Cream ______Yoghurt or dairy food (a small pot) ______Yoghurt - low fat ______Ice-cream ______Custard or milk puddings (eg rice, bread) ______Desserts (eg steamed pudding) ______Cake ______Bun, Scone or Muffin ______Condensed milk ______Kopai (Samoan cocoa) ______Chocolate or chocolate bar (eg Moro, Crunchie) ______Health or Muesli bar (eg: Muesli slice) ______Nuts (eg: peanuts ______Potato crisps ______Twisties, cheezels, popcorn ______Lollies (small packet) ______

Please name any other dairy foods, sweets or snacks eaten regularly

______

REMEMBER TO BRING THIS QUESTIONNAIRE WHEN YOU COME FOR YOUR FREE HEALTH CHECKUP.

Appendix III:

Physical Activity Questionnaire

Appendix III: Physical Activity Questionnaire

TONGA 1998 PHYSICAL ACTIVITY SURVEY

1. What is your main daily job (eg. farm worker, office worker, nurse, housework): ...... 2. How many days a week do you do this? ......

3. Rate daily work activities according to the following scale: Perceived exertion rating Hot Breathlessness Sweating 0 no no no 1 mildly mildly no 2 yes yes some 3 yes yes a lot

Activity Duration Perceived exertion rating eg. typing 4 hours 0

1 eg. lifting heavy boxes 2 /2 hours 3

……………………………………………………………………………………………………………………………… ……………………………………………………………………………………………………………………………… ……………………………………………………………………………………………………………………………… ……………………………………………………………………………………………………………………………… ……………………………………………………………………………………………………………………………… ..

4. What are your main sporting and other physical activities? Activity Frequency Duration Perceived exertion rating eg. basketball twice a week 45 mins 3 eg. playing with children every day 1 hour 2

TONGA 1998 HEALTH PROMOTION SURVEY

1. Have you heard anything about diabetes?...... YES/NO

2. If yes, where did you hear it? radio doctor other hospital staff teacher television health officer health education officer church/church group newspaper nurse pamphlet relative/friend magazine dietitian drama social club, please state: ...... other, please state: ......

3. Where would you like to learn about diabetes from? radio doctor other hospital staff teacher television health officer health education officer church/church group newspaper nurse pamphlet relative/friend magazine dietitian drama social club, please state: ...... other, please state: ......

4. Do you think there is anything you can do to reduce your chances of getting diabetes?....YES/NO

5. If yes, please state: ......

Appendix IV:

Food Items - Portion Sizes and Frequency

Appendix IV: Food Items - Portion Sizes and Frequency

Meal Food Amount Freq Note Q1 Hamburger patty,frozen,grilled 20g N Hamburger Q1 Fried chicken,indo,re 220g 4Y Fried Chicken Q1 Pizza,ham&pineapple,froz,baked 150g N Pizza Q1 Combination chow mein,chinese 220g N Chinese food Q1 Fish,unspec type,floured,fried 150g 4Y Fried fish Chips, potato or Q1 Potato chips,commercial 1cup N french fries

Q2 Apple,delicious,raw,unpeeled 1Average 4Y Fresh apple/pear Q2 Orange,navel,raw,peeled 1Whole 4Y Fresh citrus Q2 Banana,sugar type,raw,peeled 1Average 4Y Fresh Banana Q2 Melon,honey dew,raw,peeled 1cup 4Y Fresh Melon Q2 Apricot,raw 1Whole 1M Fresh stone fruit Q2 Kiwifruit,raw,peeled 1Average N Fresh Kiwi fruit Q2 Pineapple,raw,peeled 1Slice 4Y Fresh Pineapple Fresh mango, Q2 Pawpaw,raw,peeled 1cup 1W pawpaw or breadfruit Q2 Grape,green sultana,raw 80g 4Y Fresh grapes Tinned fruit with Q2 Fruit salad,can-syrup .5cup N sugar Tinned fruit without Q2 Fruit salad,tropical,can-hs,dr .5cup N sugar Q2 Apple,stewed,added sugar .5cup N Stewed fruits Q2 Mixed fruit,dried 80g N Dried fruits Q2 Banana,sugar type,raw,peeled 1Average 4Y Fresh Plaintains Q2 Lychee,raw,peeled 1Average N Fresh Tava Q2 Guava,hawaiian type,raw .5Average N Fresg Guava

Q3 Milk,whole,fluid,uht 1cup N Glass of Milk MilkShake or Q3 Milk,flavoured,chocolate,fluid 1cup N thickshake Q3 Cordial,lime juice,prepared 1cup 12W Glass of cordial Q3 Sugar,white 1tb N Add to drink Q3 Sugar,brown 5g 12W Add to drink Glass of fruit drink Q3 Cordial,citrus juice 25% 1cup N (Raro) Q3 Sugar,white 1tb N Add to drink Q3 Sugar,brown 5g N Add to drink Glass of sweetened Q3 Fruit drink,orange 1cup N fruit juice Glass of pure fruit Q3 Juice,lemon,fresh 1cup 4W juice Q3 Soft drink,lemonade 1cup 1M Glass of fizzy drink

Q3 Soft drink,low energy 1cup N Glass of low-cal drink Q3 Wine,white,medium dry 1cup N Glass of wine Q3 Sherry,unspecified type 1cup N Glass of Sherry Q3 Port 1cup N Glass of port Q3 Whisky 1cup N Serve of spirits Large bottle or jug of Q3 Beer,regular alcohol,unsp type 1cup N beer Q3 Beer,bitter or draught 1cup N Can or stubbie of beer Can or stubbie of low Q3 Beer,low alcohol 1cup N alcohol beer Q3 Water,plain,drinking 1cup 2D Glass of water Q3 Coconut water,cavity fluid 1cup 3M Coconut juice

Q6 & Q7 Tea,ceylon,ready to drink 1tsp 3D Cup of tea Q6 & Q7 Milk,whole,fluid,uht 1tsp 0% milk with tea Q6 & Q7 Milk,skim,fluid 1tsp 0% milk with tea Q6 & Q7 Milk,sweet condensed,whole,can 1tsp 3D milk with tea Q6 & Q7 Milk powder,whole 1tsp 0% With tea Q6 & Q7 Sugar,white 1tsp 0% sugar with tea Q6 & Q7 Sugar,brown 5g 6D Q6 & Q7 Coffee powder,instant 1tsp N Cup of Coffee Q6 & Q7 Milk,whole,fluid,uht 1tsp N milk with coffee Q6 & Q7 Milk,skim,fluid 1tsp N milk with coffee Q6 & Q7 Milk,sweet condensed,whole,can 1tsp N milk with coffee Q6 & Q7 Milk powder,whole 1tsp N With tea Q6 & Q7 Sugar,brown 5g N brown sugar with tea Q6 & Q7 Sugar,white 1tsp N sugar with coffee Cup of coffee Q6 & Q7 Coffee substitute,rtd 1tsp N substitute (eg Inka) milk with coffee Q6 & Q7 Milk,whole,fluid,uht 1tsp N substitute milk with coffee Q6 & Q7 Milk,skim,fluid 1tsp N substitute milk with coffee Q6 & Q7 Milk,sweet condensed,whole,can 1tsp N substitute Q6 & Q7 Milk powder,whole 1tsp N milk with cup Q6 & Q7 Sugar,brown 5g N Brown sugar wiith sugar with coffee Q6 & Q7 Sugar,white 1tsp N substitute Cup of Milo, cocoa or Q6 & Q7 Milo,powder 1tsp 6W chocolate Q6 & Q7 Milk,whole,fluid,uht 1tsp 0% milk with Milo Q6 & Q7 Milk,skim,fluid 1tsp 0% milk with Milo Q6 & Q7 Milk,sweet condensed,whole,can 1tsp 6W milk with milo Q6 & Q7 Milk powder,whole 1tsp 0% Milk with milo Q6 & Q7 Sugar,brown 5g 12W sugar with milo Q6 & Q7 Sugar,white 1tsp N sugar with Milo

Cup of Moengalo Q6 & Q7 Tea,herbal,ready to drink 1tsp N (Lemon Grass) milk with coffee Q6 & Q7 Milk,whole,fluid,uht 1tsp N substitute milk with coffee Q6 & Q7 Milk,skim,fluid 1tsp N substitute Q6 & Q7 Milk,sweet condensed,whole,can 1tsp N milk with herbal tea Q6 & Q7 Milk powder,whole 1tsp N milk with cup Q6 & Q7 Sugar,brown 5g NN sugar with cup Q6 & Q7 Sugar,white 1tsp N sugar with cup Q6 & Q7 Q8 Meat pie,individual size 1Pie N Meat pie Q8 Bacon,breakfast rasher,fried 1Rasher N Bacon Hamburger (home Q8 Hamburger with egg 1Average N cooked) Q8 Beef,chuck steak,simmered,l&f 1cup N Steak with fat Q8 Beef,chuck steak,simmered,lean 1cup N Steak with little fat Q8 Beef,mince,regular,simmered,dr 1cup N Mince dishes Q8 Veal schnitzel,frozen,fried 150g N Weiner schnitzel Q8 Pork,boneless,unsp,cooked,50%tr 220g 4Y Pork with little fat Q8 Pork,boneless,unsp,cooked,fat 220g 4Y Pork with fat Q8 Lamb,boneless,unsp,raw,75%tr 220g N Mutton with less fat Q8 Lamb,chop,unspec,grilled,l&f 220g 4Y Mutton with fat Q8 Pork,boneless,unsp,cooked,fat 150g 4Y pork with fat Q8 Pork,boneless,unsp,cooked,50%tr 150g 4Y Pork with less fat Q8 Beef,steak,unsp,roast,lean&fat 150g N Roast beef Q8 Lamb,shoulder,baked,l&f 220g N Roast lamb Q8 Chicken,drumstick,bak,lean&skin 220g 6W Fried or roast chicken Boiled or steamed Q8 Chicken,uns,rot,comm,lean&skin 220g 6W chicken Q8 Sausage,deep fried,commercial 1Average 4Y Sausages Q8 Beef stew-onion,carrot,home 220g N Stew/casserole Q8 Beef,brisket,boiled,l&f 220g N Brisket Q8 Mutton stew&potato,home prep 220g 4Y Mutton flaps Q8 Beef,corned,50%trimmed 220g N Povi Masima Q8 Beef,corned,canned 80g 4Y Tinned corned beef Q8 Ham,unspec type,non-canned,l&f 60g N Cold meat Q8 Chicken,liver,fried 40g N Organ meats Q8 Pate de foie 1Slice N Pate Fish boiled, steamed Q8 Fish,unsp,steamed 150g 3W or grilled Fish battered, fried Q8 Fish,unsp,batter,deep fried,hp 150g 6W (home cooked) Q8 Fish,unspecified type,raw 1Fillet 2W Raw fish Q8 Tuna,canned in oil .5Can 2W Tinned fish Q8 Oyster,raw 150g N Shellfish Q8 Gravy powder,prepared 40g 4Y Gravy

Q8 Butter,regular 1tb N with butter Q8 Dripping,beef 10g 4Y with dripping Q8 Oil,soybean 1tb N with vegetable oil Q8 Sauce,cheese 20g N Cheese sauce Q8 Sauce,tomato,commercial 20ml N Tomato sauce Q8 Frankfurt,simmered 1Average 4Y Hot dog Q8 Sausage roll,individual size 1Roll N Sausage roll

Q13 Tomato,common,raw 1Average N Tomato Q13 Lettuce,common,raw 1Leaf N Lettuce or celery Cabbage, brussel or Q13 Cabbage,common,unsp,boiled .5cup N brocolli Q13 Silverbeet,boiled .5cup N Silverbeet or Spinach Q13 Carrot,unsp,peeled,boiled .25cup N Carrots Q13 Cauliflower,boiled 1Piece N Cauliflower Q13 Avocado,raw 1Halves N Avocado Capscicum or green Q13 Capsicum,unspec type,boiled .25cup N peppers Q13 Onion,mature,brown,peeled,boil 5g 1D Oniions Q13 Asparagus,boiled 1Spear N Asparagus Q13 Bean,broad,boiled .25cup N Green beans Q13 Pea,green,canned,drained 10g N Green peas Cucumber, courgette Q13 Cucumber,common,raw,peeled 1Slice N or marrow Q13 Mushroom,golden,asian,can,br,dr 5g N Mushrooms Q13 Sweet corn,frozen,boiled .25cup N Sweetcorn Q13 Watercress,raw .25cup N Puha or Watercress Q13 Sweet potato,unsp,peeled,boiled 250g 4Y Kumara Q13 Pumpkin,unsp,peeled,boiled .25cup N Pumpkin Boiled or Mashed Q13 Potato,mashed,dried,home prep 1cup N potato Q13 Potato,pale skin,baked,flesh 250g N Roast or Baked potato Chip potato (home Q13 Potato chips,home prepared 1Pods N cooked) Beetroot (fresh, Q13 Beetroot,canned,drained 1Slices N tinned) Q13 Parsnip,peeled,boiled .25cup N Parnip or swede Q13 Taro,peeled,boiled 250g 4Y Yam or taro tuber Taro leaf (eg Q13 Spinach,english,boiled 1cup 2W palusami) Q13 Bean sprouts,raw 10g N Beans sprouts Q13 Coconut cream 20g 4W Coconut cream Q13 Banana,unspec type,raw,peeled 1Average 4Y Green banana Q13 Spinach,english,boiled 1cup 4W Pele Leaves Q13 Cassava,peeled,boiled 1Whole 4Y Cassava Q13 Taro,peeled,boiled 1cup 4Y Giant Taro (Kape) Q13 Taro,peeled,boiled 1cup 4Y Breadfruit (mei)

Green Plaintains Q13 Banana,common,raw,peeled 1Average 1D (Hopa)

Q19 Weet-bix 25g N Breakfast Cereals Q19 Sugar,white 1tb N Add to Cereals Q19 Sugar,brown 5g N Add to cereals Q19 Corn flakes 25g N Breakfast Cereals Q19 Biscuit,bran 1Biscuit N Bran Plain Biscuits ( eg Q19 Biscuit,plain,sweet 1Biscuit 4Y Arrowroot) Q19 Biscuit,chocolate-coated 1Biscuit 4Y Fancy Biscuits Q19 Crumpet,regular 1g N Crumpets Q19 Cracker,water 1Biscuit 28M Cabin Bread Crispbread or Q19 Cracker,flaky 1Biscuit N crackers Q19 Pancake,home prepared 1Small 30M Pancake Doughboy (Maori Q19 Dumpling 150g N dumpling) Q19 Peanut butter,unspecified type 1tb N Peanut butter Q19 Vegemite 1tb N Vegemite or marmite Honey, jam or Q19 Jam,unspecified type 1tb 10W marmalade Mayonaise or salad Q19 Mayonnaise,commercial 2tb 4Y dressing Q19 Fried rice,chin,re 200g N Fried rice Q19 Rice,white,boiled 1cup 2W Boiled rice Chines Food ( home Q19 Combination chow mein,chinese 250g N cooked) Q19 Pizza,unspec type,home prepared 120g N Pizza (home cooked) Pasta(eg spaghetti, Q19 Rice noodle,asian,boiled 120g 4Y macaroni, noodles) Q19 Baked beans,can-tomato sauce .25cup N Baked beans Other beans (eg Soya, Q19 Bean,lima,dried,boiled .25cup N lima) Q19 Pea,split,dried,boiled .25cup N Split peas or lentils Q19 Soup,cream of chicken,can 220g N Creamed soup Q19 Soup,minestrone,home prepared 220g 4Y Other soup Q19 Dumpling 150g 4Y Tongan Dumpling Q19 Cassava,peeled,boiled 1Whole N Manioke Tama Toókutu (flour Q19 Cassava,peeled,boiled 1Whole N products) Q19 Oats,rolled,cooked 1cup N Porridge

Q20 & Q21 Bread,white,regular 1Slice 10W Bread & Butter Q20 & Q21 Bread,brown 1Slice N Q20 & Q21 Bread,wholemeal 1Slice N Q20 & Q21 Butter,regular 1tsp 10W

Q20 & Q21 Margarine,table,regular 1tsp N

Q23 Egg white,hard-boiled 32g 1M If you ate eggs? Q23 Egg,scrambled 32g N Q23 Egg,fried 32g N

Q24 Cheese,cheddar,processed 1Slice N Cheese Q24 Cheese,cottage 1tb N Cottage cheese Cream cheese or Q24 Cheese spread,cream cheese 1tb N cheese spread Q24 Cream,thickened,uht .25cup N Cream Yoghurt or dairy food Q24 Yoghurt,natural 1Average N (a small pot) Q24 Yoghurt,low fat,natural 1Average N Yoghurt -low fat Q24 Ice cream,standard type 1Scoops 4Y Ice -cream custard or milk puddings ( eg rice, Q24 Custard,commercial 1cup N bread) Desserts ( eg steamed Q24 Pudding,sponge,steamed,home 100g N pudding) Q24 Cake,chocolate,home prepared 1Slice N Cake Q24 Scone,plain,home prepared 1Average N Bun, Scone or Muffin Q24 Milk,sweet condensed,whole,can 5g 2D Condensed milk Chocolate or chocolate bar ( Moro, Q24 Chocolate,candy-coated 1Packet N crunchie) Health or Muesli bar ( Q24 Muesli bar,fruit 1Bar N eg Muesli slice) Q24 Peanut,roasted with skin,salted 50g 4Y Nuts ( eg peanuts) Q24 Potato crisps,flavoured 1Packet N Potato crisps Twisties, cheezels, Q24 Extruded snack,cheese flavoured 1Packet N popcorn Q24 Boiled sweets 1Items N Lollies ( small packet)

Note: Frequency Letter stands for N : Never D: Amount per Day Y: Amount per Year (Rarely - once a quarter W: Amount per Week

Appendix V:

Recipes – Ingredients and amounts (Dignan et al. FAO 2004)

Appendix V : Recipes – Ingredients and amounts (Dignan et al. FAO 2004)

Pancake, hope prepared

Ingredients Weight (g) Flour 283 Sugar 28 Salt 1 Water 795

Rice with Coconut Cream

Ingredients Weight (g) Rice 227 Coconut cream 213 Water 568

Taro leaves

Ingredients Weight (g) Taro leaves 500 Salt 5 Onioni 10 Garlic 5 Water for boiling

EGG, chicken fried

Ingredients Weight (g) Eggs 120 Cooking oil 5 Salt 1

CURRY CHICKEN, without bones

Ingredients Weight (g) Chicken, dices 1000 Onioni 50 Garlic 1 Oil for frying 15 Chilli powder 1.5 Tomatoes 120 Salt to taste

PALUSAMI, taro leaves & coconut cream

Ingredients Weight (g) Taro leaves 1000 Concentrated coconut cream 850 Onioni 30

PALUSAMI, taro leaf, coconut cream & corned beef

Ingredients Weight (g) Taro leaves 1000 Concentrated coconut cream 850 Corned beef 375 Onioni 30

PIG, baked

Ingredients Weight (g) Pig meat 2000 Garlic 20 Crushed ginger 20 Salt 10 Onioni 20

PIG, flesh boiled

Ingredients Weight (g) Pig meat 1000 Garlic 10 Crushed ginger 20 Salt 10 Onioni 20