diabetes mellitus and sugar consumption; an ecological study · diabetes mellitus and sugar...

Diabetes mellitus and sugar consumption; an ecological study

Muhammad Talha Khan

2011

Supervisor: Prof. Urban Janlert (MD, Professor of Public Health, specialist in Social Medicine. Deputy Head of Division.)

In the name of God, the most beneficent,

the most merciful

“I dedicate this thesis to my beloved parents

for their endless love, support and encouragement.”

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Acknowledgements

I am heartily thankful to my supervisor, Prof. Urban Janlert for his support and motivation throughout my research process.

I would like to express my gratitude to DR. Nawi N.G (MD, MPH, PhD. Senior lecturer in Epidemiology) for his valuable comments and suggestions.

I owe thanks to my elder brother Taha and my family, for their love, prayers and support.

I appreciate all of my friends who made my stay in Sweden, wonderful.

I am also thankful to the Umea University for providing me an opportunity to study here. Lastly, I offer my regards and blessings to all of those who supported me in any respect during the completion of my Masters degree.

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Table of content:

Acknowledgement--------------------------------------------------------------- iii

List of terms--------------------------------------------------------------------- iiii

List of abbreviation-------------------------------------------------------------iiii

List of charts --------------------------------------------------------------------- ix

List of tables---------------------------------------------------------------------- ix

1. Introduction --------------------------------------------------------------------1

1.1. Diabetes-----------------------------------------------------------------------1

1.1.1. Definition------------------------------------------------------------------1

1.1.2. Pathophysiology-----------------------------------------------------------1

1.1.3. Commonly occurring types------------------------------------------------ 2

1.1.3.a. Type 1 diabetes mellitus----------------------------------------------- 2

1.1.3.b. Type 2 diabetes mellitus----------------------------------------------- 2

1.1.3.c. Complications------------------------------------------------------ 3

1.1.4. Global burden of diabetes-----------------------------------------------------4

1.1.5. Morbidity and mortality associated with diabetes--------------------- 6

1.1.6. Global expenditure on diabetes---------------------------------------6

1.2. Sugar consumption and diabetes mellitus----------------------------------7

1.3. Global sugar consumption--------------------------------------------------9

1.4. Other risk factors and prevalence of diabetes mellitus-------------------10

2. Objectives---------------------------------------------------------------------- 11

3. Methodology-------------------------------------------------------------------11

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3.1. Study design---------------------------------------------------------------- 11

3.2. Independent variables----------------------------------------------------- 11

3.3. Dependent variable-------------------------------------------------------- 11

3.3.1. WHO diagnostic criteria for diabetes------------------------------------ 12

3.4. Data collection------------------------------------------------------------- 12

3.4.1. Data for sugar consumption------------------------------------------ 12

3.4.2. Data for diabetes mellitus-------------------------------------------- 13

3.4.3. Data for Urban Living------------------------------------------------ 15

3.4.4. Data for gross national income---------------------------------- - 15

3.4.5. Data for percentage out of pocket payment---------------------- 15

3.5. Analysis -------------------------------------------------------------------- 16

3.5.1. Descriptive analysis -------------------------------------------------- 16

3.5.2. Statistical analysis-----------------------------------------------------16

4. Results------------------------------------------------------------------------- 16

4.1. Results for the trends of sugar consumption and diabetes mellitus ------ 17

4.2. Results for comparison of diabetes mellitus prevalence between year 2007 and 2010 in six WHO regions and between regions ------------------------------20

4.3. Results for the comparison of the diabetes mellitus prevalence between year 2007 and 2010 within each of the six different regions----------------------21

4.4. Results for the analysis of association between sugar consumption, urbanization and Diabetes Mellitus prevalence in 144 WHO member state and within each WHO region---------------------------------------------------------- 28

5. Discussion -------------------------------------------------------------------- 33

6. Recommendations ---------------------------------------------------------- 35

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7. Conclusion --------------------------------------------------------------------36

References ----------------------------------------------------------------------- 37

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Abstract:

Introduction: Today, chronic non communicable diseases including diabetes, which are

correlated with common modifiable risk factors such as an unhealthy diet, are a primary

concern of human life and its development. There is escalating disability and substantial

economic burden in nearly every country because of diabetes and its complications, and it has

become one of the leading health issues in this century. There is a possibility that diabetes

mellitus can be triggered due to increased sugar consumption; as it is known that sugars,

especially glucose, have high glycemic index, and when sugar is consumed in increased

amounts, there is a possibility of increased and stressful insulin secretion by the pancreas due to

its high glycemic index, which can lead to type 2 diabetes mellitus.

Objectives: To analyze the association between sugar consumption and the prevalence of

diabetes mellitus in 144 WHO member states and within each WHO region.

Methodology: For the independent variable, namely sugar consumption per capita in

kilograms, data was taken from the Sugar Year Book 2008. For the independent variable urban

living percentage which is used as a proxy variable for confounders, data was taken from the

World Health Statistics 2010. For the dependent variable, which is the prevalence of diabetes

mellitus percentage among people aged 20 to 79 years old, data was taken from the

International Diabetes Atlas (IDA) 2003 and IDA 2007 and for the year 2010, data was taken

from the International Diabetes Federation website site: www.idf.org. Data was then analyzed

by using statistical software STATA 10.

Results: This study showed an increasing trend of the prevalence of diabetes mellitus among

people aged 20 to 79 years old from 2003 to 2010, as well as of sugar consumption per capita

from 2000 to 2007 in five of the WHO regions, with exception of the European region where

there was a slight decrease in both variables. Comparisons of the prevalence of diabetes mellitus

between the regions positioned the Eastern Mediterranean region at the highest place followed

by the American, Western Pacific, European, South East Asian and African regions respectively.

Analysis has shown a significant positive association between the prevalence of diabetes mellitus

and sugar consumption after controlling for confounding, when the averages of all three

variables for 144 countries were used to perform linear regression. However, when linear

regression is performed separately for each region, all of the six regions showed positive

association between sugar consumption and diabetes mellitus, but the result was significant

only for the European region, while insignificant for the remaining five regions.

A positive association was seen between the prevalence of diabetes mellitus and urbanization.

Urbanization was used as the proxy variable for confounders. In three regions, there were

positive correlations, which was significant for the African region but insignificant for the

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Eastern Mediterranean and the Western Pacific regions. The remaining three regions showed a

negative association between the prevalence of diabetes mellitus and urbanization. The result

was significant for the American region, while insignificant for the European and South East

Asian region.

Conclusion: The prevalence of diabetes mellitus appeared to be increasing with time which was apparently linked to modifiable risk factors, such as sugar intake. Diabetes prevalence was also associated with urbanization, which was used as a proxy for various risk factors, such as increased consumption of junk food, obesity and physical inactivity. There is a need to address this issue on the global level, because the impact of this non communicable chronic disease is substantial, and together with its complications, it will result in disability and premature deaths around the world. This global burden of diabetes is in turn, hampering the economic growth and stability, throughout the world.

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List of Terms:

Comparative prevalence: Age adjusted prevalence.

Ectopic Lipids: Lipids which are not in their usual position.

Glycemic Index: is a measure of the effects of the carbohydrates on the blood sugar levels.

Glycemic Load: is a ranking system for the carbohydrate content in a food portions, based on their glycemic index and the portion size.

Hypertryacylglycerolemia: Increased levels of the triacylglycerides in the blood above a normal limit.

Hepatic: Related to the liver.

Lipids: Fat molecules.

Lipogenesis: Synthesis of the fatty acids in the body from the glucose and other substrates.

Metabolic Syndrome: Combination of medical disorders that can lead to diabetes and cardiovascular diseases.

Steatosis: Abnormal accumulation of the lipids within the cells.

Triglycerides: Component of VLDL.

Visceral Fat: Fat attached to the organs.

Plasma: component of the blood.

List of Abbreviations:

AFRO: African region.

AMRO: American region.

BMI: Body Mass Index.

DM: Diabetes mellitus

EMRO: Eastern Mediterranean region.

EURO: European region.

IDF: International Diabetes Federation.

ISO: International Sugar Organization.

NCDs: Non communicable diseases

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SEARO: South East Asian region.

UAE: United Arab Emirates.

VLDL: Very low density lipo proteins.

WPRO: Western Pacific region.

List of charts:

Chart 1: Trend of the sugar consumption in the six WHO regions from 2000 to 2007 ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 16

Chart 2: Trend of the prevalence of diabetes mellitus among 20 to 79 years old in the six WHO regions during 2003, 2007 and 2010. ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 17

Chart 3: Average diabetes mellitus prevalence among 20 to 79 years old in the six WHO regions during 2007 and 2010. ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐ 18

Chart 4: Diabetes mellitus prevalence among 20 to 79 years old in the AFRO during 2007 and 2010.‐‐‐‐20

Chart 5: Diabetes mellitus prevalence among 20 to 79 years old in the AMRO during 2007 and 2010.‐‐‐21

Chart 6: Diabetes mellitus prevalence among 20 to 79 years old in the EMRO during 2007 and 2010.‐‐‐22

Chart 7: Diabetes mellitus prevalence among 20 to 79 years old in the EURO during 2007 and 2010.‐‐‐‐23

Chart 8: Diabetes mellitus prevalence among 20 to 79 years old in the SEARO during 2007 and 2010.‐‐‐24

Chart 9: Diabetes mellitus prevalence among 20 to 79 years old in the WPRO during 2007 and 2010.‐‐‐25

List of tables:

Table 1: Global burden of the diabetes in 2010 and its projection in 2030.------------------------ 4

Table 2: Analysis using linear regression, for the association between sugar consumption, urbanization and the prevalence of diabetes mellitus, in 144 WHO member states, using STATA 10.-----------------------------------------------------------------------------------------------------------26

Table 3: Analysis using linear regression, for the association between sugar consumption, urbanization and the prevalence of diabetes mellitus within AFRO, AMRO and EMRO, using STATA 10.--------------------------------------------------------------------------------------------------27

Table 4: Analysis using linear regression, for the association between sugar consumption, urbanization and the prevalence of diabetes mellitus within EURO, SEARO and WPRO, using STATA 10.--------------------------------------------------------------------------------------------------28

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1. Introduction:

Today, non communicable diseases (NCDs) including diabetes are a primary concern of human life and its development. In developing countries approximately eight to fourteen million people die every year prematurely because of NCDs that are preventable. The most commonly occurring NCDs are cardiovascular diseases, diabetes, chronic respiratory disease and cancer. Due to these NCDs people are dying prematurely which are caused by modifiable risk factors such as harmful diet and other risk factors, all of which can be prevented (1).

According to WHO, in the coming decade the mortalities due to health problems will rise by 17 % globally. This increase will be more pronounced in low and middle income countries, mostly in the African and Eastern Mediterranean region, where the increase will be 27% and 25% respectively. NCDs will cause approximately 80% of the mortalities in developing countries and if this issue is not addressed then the deaths and burden of disease from NCDs, together with diabetes, will rise continuously (1).

An important question is whether diabetes mellitus can occur due to increased sugar

consumption. As it is known that sugars especially glucose have high glycemic index, and when

sugar is consumed in increased amounts, there is a possibility of increased and stress full insulin

secretion by the pancreas due to the high glycemic index of glucose, which can lead to type 2

diabetes mellitus (2). Currently, sugar is utilized in increased amounts especially in the form of

soft drinks and other items such as confectionary products. This study aims to observe the

trends of sugar consumption together with the trend of the prevalence of diabetes mellitus in the

last decade and to observe the association between them.

1.1 . Diabetes:

1.1.1 Definition:

Diabetes is a non communicable chronic disease with raised blood glucose levels (hyperglycemia) due to decreased production of insulin by the pancreas or the inability of cells to utilize insulin properly (3, 4).

1.1.2. Pathophysiology:

The hormone insulin is responsible for the mobilization of glucose into the cells of human body from blood, mostly in muscles and fat tissues, where glucose is utilized as the source of energy. Source of glucose are foods which are rich in carbohydrates and the most commonly present carbohydrates in human diet are disaccharides mainly sucrose and a polysaccharide, starch. After a meal these carbohydrates are digested and then converted into monosaccharide glucose,

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as a result, the blood glucose level begins to rise and in turn the pancreas releases insulin. These insulin molecules, after reaching the cells, attach themselves to the insulin specific receptors, which open the specific channels, to allow the entry of glucose into the cells, and then the glucose is utilized as a principle source, for energy production (5, 6).

As a result of insulin secretion by the pancreas and subsequent glucose uptake by the cells of the body, blood glucose level decreases, which in turn decrease the insulin secretion by the pancreas. In diabetes there is a decrease in insulin production by the pancreas or there is insulin inaction, causing hyperglycemia. Both of these conditions that are decrease insulin production, and insulin inaction can also occur simultaneously in diabetes (7, 6).

1.1.3 Commonly occurring types:

1.1.3. a. Type 1 diabetes mellitus:

In Type 1 diabetes mellitus there is a decrease in insulin production by the pancreas; therefore insulin administration is mandatory to maintain blood glucose levels, as insulin allows entry of glucose into the cells and decreases raised blood glucose levels. This type of diabetes mellitus was previously known as childhood or juvenile diabetes mellitus and also as insulin dependent diabetes mellitus. Type 1 diabetes mellitus can be autoimmune or idiopathic (without known etiology) (8, 6).

Symptoms of diabetes mellitus are:

• Polyuria (increased urine excretion). • Polydipsia (excessive thirst). • Polyphagia (increased hunger). • Loss of weight. • Changes in vision. • Fatigue. (8, 6).

1.1.3. b. Type 2 diabetes mellitus: Type 2 diabetes mellitus was previously known as non insulin dependent diabetes mellitus or diabetes of adult onset. This is the most common type of diabetes; ninety percent of all diabetic patients have type 2 diabetes mellitus around the world. Patient with type 2 diabetes is resistant to insulin´s action and there is also a relative insulin deficiency, but comparatively less as compare to type 1 (8, 9, 6). In the beginning, patients with type 2 diabetes do not require insulin and some cases do not need insulin throughout their lives. In type 2 diabetes mellitus, most of the times hyperglycemia

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is not enough to produce symptoms of diabetes and therefore this type of diabetes remains undiagnosed for years. But this condition leads to increased risk of developing complications of diabetes. Symptoms in this type of diabetes are similar to those of type 1 diabetes mellitus, and they become apparent only when hyperglycemia gets severe. The specific cause for this type of diabetes is not known. Nevertheless the risk factors for developing type 2 diabetes are obesity, old age, physical inactivity, race and genetics of a person (8, 9, 6). Diabetes mellitus can also occur due to increased sugar consumption. Study of Montonen and coworkers state that, sugars especially glucose have high glycemic index, and when sugar is consumed in increased amounts, there is a possibility of increased and stress full insulin secretion by the pancreas (2). 1.1.3.c. Complications: Uncontrolled diabetes can lead to various complications which include diseases of the cardio vascular system, kidneys and eyes. Diabetes also causes damage to the peripheral nervous system (in which the patient loses sensations at the periphery of limbs), that can lead to the amputation of limbs (10, 6).

Figure 1: Leg amputation because of prepheral neuropathy (11).

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1.1.4. Global burden of diabetes mellitus: Diabetes is among the most common chronic non communicable diseases around the world. It is ranked between fourth or fifth of the foremost causes of death nearly in all affluent countries, and it is also becoming an epidemic in many middle and low income countries. There is an escalating disability and substantial economical burden in almost every country because of diabetes and its complications. Diabetes has become one of the leading health issues in this century (12). Table 1: Global burden of the diabetes in 2010 and its projection in 2030 (13).

Table 1 demonstrates that, out of 4.3 billion people in the age group 20-79 years, 6.4% or 285 million people have diabetes, which will rise to 7.7% or 438 millions in 2030, as the population size grows.

Studies based on populations for diabetes have shown that a considerable amount of diabetic patients have been found who were not diagnosed previously. This is because the patients remained symptomless for years, especially in the case of type 2 diabetes mellitus. They become evident when blood testing is performed on a mass scale (12).

Year

2010 2030

Total world population (billions) 7.0 8.4

Adult population (20‐79 years, billions) 4.3 5.6

Diabetes mellitus in (20‐79 years old)

Global prevalence (%) 6.6 7.8

Age adjusted prevalence (%) 6.4 7.7

Number of people with diabetes (millions) 285 438

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Figure 2: Global prevalence percentage of diabetes mellitus among 20 to 79 years old people in 2007 (14).

In 2007 countries which have the highest prevalence of diabetes mellitus of 14% to 20% are UAE and Saudi Arabia, in figure 2. Countries which have the prevalence of 10% to 14% are Egypt, Oman, Jordan, Lebanon, Malaysia, Mexico, Jamaica, Nicaragua, Suriname and French Guiana. Countries which have the prevalence of diabetes mellitus between the ranges of 8% to 10% are Pakistan, Afghanistan, Israel, Algeria, Morocco, Guyana, Belize, Honduras, El Salvador and Cuba (14). It is possible that low prevalence also could be the result of low diabetes screening activity.

There are many countries that have the prevalence of diabetes mellitus between 6% to 8%, some of them are India, USA, Canada and Russia. Many countries have the prevalence between an array of 4% to 5% like China and Australia. Countries that have the lowest prevalence of less than 4% includes majority of the African countries together with Mongolia and UK (14).

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1.1.5. Morbidity and mortality associated with diabetes:

Approximately four million deaths attributed to diabetes were estimated around the globe, among the people of age 20-79 years, in 2010. This figure is about 6.8% of the total deaths among all age groups in the world during 2010. Diabetes caused 6% of deaths in the Africa and accounted 15.7% of deaths in the North America, among adults, in the same year (15, 16).

Premature deaths are increasing due to diabetes and this condition appears to become worse, especially in the low and middle income countries. These premature deaths are of same extent, to the deaths from infectious diseases in this age group. Most populated countries like China, India, USA and Russia are expected to have the highest numbers of deaths attributed to the diabetes, because they have the largest numbers of the diabetic patients in the world (15, 16).

Recent studies have reported that the women with diabetes have relatively higher risk of death than the diabetic men. Diabetic women were anticipated to have the higher share of deaths because of diabetes and its complications than the diabetic men, in 2010. This higher share of female deaths was present in all regions of the world, attaining 25% of all deaths among the middle aged women in some regions (15, 16).

1.1.6. Global expenditure on diabetes:

Substantial economic burden is imposed by diabetes, globally. Approximately, 11.6% of the entire health spending of the world is expected to be used for treating diabetic patients alone, in 2010. In the same year, nearly 376 billion US dollars expenditure was predicted for the treatment and prevention of diabetes and its complications. It was also predicted that by 2030 this amount will increase by 490 US dollars, globally (17, 18).

If this amount is given in International dollars (ID), so that the difference in purchasing power is corrected, then the total world expenditure estimated for diabetes was around 418 billion ID in 2010, and expected rise is 561 billion ID in 2030. Studies predicted that, on average every person will spend 703 USD or 878 ID in the world during the year 2010 on diabetic care. In addition to this financial burden, diabetes becomes more cumbersome because of the loss of efficiency or workability of a diabetic person, which in turn hampers the economic growth globally (17).

According to the American diabetes association there was a loss of 58 billion US dollars in 2007. This is equivalent to 50% of direct health spending on diabetes, due to fewer working days, constrained workability, less efficiency, death and everlasting disability of the diabetic persons in US. This economic burden due to diabetes is higher in the low income countries compared to the rich countries because of early deaths in young age group (17).

Total losses as predicted by the WHO on countries income due to diabetes and CVDs are as follows; China about 557.7 billion ID, Russia 303.2 billion ID, and 236.6 billion ID in India. In the Brazil it is about 49.2 billion ID and 2.5 billion ID in Tanzania, during the years 2005 and

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2015. Thus it is clear that diabetes and its complications which results in premature deaths and disabilities plays an important role in this significant economic burden (17, 18).

1.2. Sugar consumption and diabetes mellitus:

A study by Montonen and coworkers in 2007 reported that; there is an increased risk of diabetes with the sugar sweetened beverages such as soft drinks and berry juices, which is in accordance with current findings in other studies (2). In 2010, Malik and coworkers also demonstrated that, there is an increased risk of type 2 diabetes mellitus and metabolic syndrome because of the sugar sweetened beverages, which is partly due to their contribution to weight gain. These effects of the sugar sweetened beverages are due to the addition of sugars as flavor in them, which are rapidly absorbable carbohydrates, in high levels (19).

There are evidences that show how sugar sweetened beverages increases the blood glucose level and the concentration of insulin very rapidly and therefore utilized in excess, this adds to an excess glycemic load. Impaired glucose tolerance and the resistance to insulin are induced by the high glycemic load especially in overweight people and this high glycemic load also increases the inflammatory biomarkers level which are related to the increase risk of type 2 diabetes mellitus (19). The results of an 8 year long cohort study of Schulze M et al in 2004, showed positive association of both (the risk of diabetes mellitus and weight gain) with the intake of sugar sweetened beverages, independent of known risk factors (20).

Study on the African American women showed that, there is a positive association between soft drinks and fruit juices consumption with the risk of type 2 diabetes mellitus. This association is somewhat stronger than the previous prospective cohort study on the US nurses named as Nurses’ Health Study 2, in which most of them were whites (21). The risk of type 2 diabetes mellitus can be increased by the sugar sweetened beverages because of the high glycemic load, which causes insulin resistance, inflammation and impaired beta cell function (22).

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Figure 4: Mechanisms linking excess fructose consumption to the metabolic syndrome (23).

Figure 4 demonstrates that, the increased use of fructose can lead to hepatic steatosis and to hyper triaacylglycerolemia. As a result of this, fats are accumulated in organs and the ectopic lipids deposit in the skeletal muscles. If this condition is prolonged, then the metabolic syndrome develops because of the visceral obesity and accumulation of toxic lipids in the muscles (23).

Improvement is seen, as the risk of type 2 diabetes mellitus decreases and the insulin response increases, when there is a decrease in the consumption of added sugars and increased fiber intake among the overweight Latino youth (24). Fructose in diet was correlated with the risk of

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type 2 diabetes mellitus occurrence in older women, as observed in a large follow up research (25). But another large scale cohort study has shown no significant correlation between the dietary fructose intakes and type 2 diabetes mellitus (26). However, very less data is available which observes long term effect of sugar intake on diabetes; there is a need of further research in this area (27).

1.3. Global sugar consumption:

The term sugar is used for the sweet crystalline carbohydrates, which are consumed by humans such as sucrose, fructose and lactose. Most commonly used among these sugars is sucrose which is extracted from sugar cane and beet. Sucrose is also known as table sugar.

History:

The English word sugar is derive from an Arabic word Sukkar which is originated from the Sanskrit word Sharkara. In ancient times sugar was produced from sugarcane in the Indian subcontinent, but at that time most of the world consumed honey as a sweetener, because sugar production was not ample and low-priced, until the Indians extracted a crystalline form of sugar from sugarcane juice. Because crystalline sugar was easy to store and transport, the Indian merchants carried it to different parts of the world and taught sugar cultivation to the Chinese (28).

It was during the agricultural revolution by the Muslims; business men from the Arabia, learned technique for the production of sugar from India and established sugar industry at large scale. Arabs were the first to set up sugar mills in the Arab Empire. They also spread its production throughout the Arab Empire including the Western Europe and the old world (28).

Crusader returning back from the Holy Land brought sugar to the Europe, and in the 12th century Venice started sugar production for export to the Europe, where honey was used as a sweetener at that time. Christopher Columbus in 1492 brought sugar cane with him, from the Spain to the America, and that’s how it reaches to the new world. Today it is produced in a substantial scale from sugar cane and sugar beet in many countries (28).

Global sugar consumption is estimated to be a little above than 160 million tons per year, with an increase of about 32 million tons during 1998 to 2010. This accounts for a growth rate of 2% per year, which is somewhat higher than a growth rate during previous decade. Estimated growth rise in the consumption of sugar is seen globally, mainly in the developing countries and to lesser extent in the high income countries (29).

During the period of past ten years till 2009, sugar utilization rate is raised by 2.5% every year on an average; this is more rapid then the global population growth rate of 1.2 %. Utilization of global sugar is decreasing in the high income countries, but it is raising in the low and middle income countries. This is partially a reflection of a tendency of buying expensive food items such

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as sweet products, as persons earnings are increasing in the low and middle income countries (30).

1.4. Other risk factors and the prevalence of diabetes mellitus:

Urbanized people are becoming more prone to chronic non communicable diseases such as diabetes mellitus, and the prevalence of diabetes is much higher among people living in cities compared to people living in rural area. Prabhakaran and collaborators in 2007 stated that their study clearly showed an increased prevalence of metabolic syndrome in the main city areas of India in comparison to the neighboring villages. This general metabolic syndrome prevalence among adults of urban area was equal to or even higher than that in the Western countries. Urbanization plays a significant role in the occurrence of metabolic syndrome because it has its role in changed life style of people (31).

Hussain and co researchers in 2005 demonstrated significant results of increased prevalence of type 2 diabetes mellitus in urban population in comparison to rural population in the Bangladesh. This risk was about three to four folds more in urban slum for both sexes. This research is in accord with other researches in the India and Bangladesh (32).

Another recent study of Mohan V and collaborators in 2008 also states that, there is a major role of urbanization in the epidemiological health transition. People of urban area have higher prevalence of diabetes in comparison to slums and rural residents. Even the non obese and physically active urban people have an increased risk of diabetes compared to the rural people in India (33).

Moreover, wealth has its influential effect, as it is evident that urban people have higher prevalence of diabetes than people of slum areas, and people of slum areas in turn have the higher prevalence of diabetes than rural people. (33). Marked lifestyle changes were also observed in the Kuwait along with hasty rise in financial well being which resulted in the increasing of chronic NCDs such as diabetes, CVDs, hypertension and stroke (34).

In Tanzania a study showed similar results of the increased prevalence of diabetes and impaired glucose tolerance in population of urban area as compared to that of rural area. There was also a difference of the risk factors for type 2 diabetes mellitus among urban and rural populations. People living in urban areas have more prevalence of the risk factors for diabetes such as physical inactivity, overweight and obesity than people in rural areas (35).

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2. OBJECTIVES:

1) To describe the trend of sugar consumption in the 144 WHO member states from 2000 to 2007.

2) To describe the trend of the prevalence of diabetes mellitus in the 144 WHO member states from 2003 to 2010.

3) To compare the prevalence of diabetes mellitus between the year 2007 and 2010 in the six WHO regions and between the regions.

4) To compare the prevalence of diabetes mellitus between the year 2007 and 2010 within each of the six different regions.

5) To analyze the association between sugar consumption and the prevalence of diabetes mellitus in 144 WHO member state and within each WHO region.

3. Methodology:

3.1. Study design:

Ecological study design is selected using an aggregate data. 193 WHO member countries in the six different regions of the world as mentioned by the WHO were selected. Out of these 193 countries, 144 countries are sorted out for which data for all 3 variables were available.

3.2. Independent variables:

The main independent variable is sugar consumption per capita. Consumption of sugar is measured in kilograms. The other independent variable is, percentage of people living in urban area, Gross national income (GNI) and percentage out of pocket payment, in each country. Data are taken from each of the 144 selected countries.

3.3. Dependent variable:

Diabetes mellitus prevalence percentage among 20 to 79 years old is taken as a dependent variable, for each of the 144 selected countries. Data are taken from the International Diabetes Atlas (IDA) published by the International Diabetic Federation (IDF). IDF preferred the WHO criteria for the screening of diabetes mellitus.

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3.3.1. Diagnostic criteria WHO and the International diabetes federation recommended following criteria for the diagnosis of diabetes mellitus: 1: Fasting plasma glucose should be greater than or equal to 7mmol/dl (126mg/dl). or 2: 2-hour plasma glucose, should be greater than or equal to 11.1mmol/l (200mg/dl) after taking 75 grams of glucose orally (36).

Oral Glucose Tolerance Test (OGTT) is the preferred procedure, recommended by the WHO and IDF, which take into account, the above mentioned criteria.

Requirements for the OGTT:-

1) For 3 days before the test carbohydrate diet is unrestricted. 2) Fasting for at least 8 hour. 3) 30 minutes rest before performing the test; person is not allowed to smoke and should

be seated during test. 4) Before and after 2 hours of 75 grams glucose intake, plasma glucose is measured. (6).

3.4. DATA COLLECTION:

3.4.1. Data for sugar consumption:

Data for sugar consumption are taken from the Sugar Year Book 2008 (37), and from the WHO website (38). This book is a publication of the International Sugar Organization (ISO). There are 84 member countries of the ISO which accounts for 82 percent of total production of sugar in the world, 66 percent of total sugar consumption, 93 percent of total sugar export and 38 percent of total sugar import around the world (37).

ISO member countries submit their statistics to the ISO under the regulations of International Sugar Agreement. Statistics of other countries are either provided by their governments, obtained from publications with statistics or anticipated (37). Data for sugar consumption is taken as per capita consumption for each country in kilograms, for the year 2001 to 2007, it is taken from the Sugar Year Book 2008, and for the year 2000, data is taken from a website: http://www.whocollab.od.mah.se/expl/globalsugar.html; source of this website is the Sugar Year Book 2005. Collected data is for the centrifuged sugars.

Some of the countries have reported data for sugar consumption in metric tons (probably they have used total sale of sugar in metric tons, as a proxy for sugar consumption, in those countries), but for some countries data was estimated on the basis of imports and exports of sugar by that country (Personal contact with ISO).

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3.4.2. Data for diabetes mellitus:

Data for the prevalence of diabetes mellitus for each country are taken from the IDA for the year 2003 and 2007 (39, 40), published by the IDF. Data for the prevalence of diabetes mellitus for 2010 is taken from the website of IDF www.idf.org.(45).

IDF used the following method of data collection in order to assess the prevalence of diabetes:

1:- Literature search was done to identify studies with prevalence figures. Local IDF member organizations were also contacted for that purpose. Researchers of diabetes, in the main IDF geographical region, were contacted and asked for providing information on diabetes prevalence for countries within their geographical area. Members of the IDF association were also asked for relevant data by the IDF (39, 40). Different sources were used to obtain information about diabetes prevalence, for example, surveys of diabetes prevalence, registers, statistics from hospitals, estimates of the government etc (39, 40). Reliability of a study was assessed by following criteria by the IDF:-

• Studies for the most recent year were preferred. • Preferred method of diabetes screening was oral glucose tolerance test (OGTT), then two

hour blood glucose level only, followed by fasting blood glucose level only and the least preferred method was self reporting.

• Studies based on large samples with high response rate were selected. • If there were more than one study from a country with no obvious superiority over

another then an average of the results was calculated from the available studies and applied to national population afterwards (39, 40).

2:- Prevalence rates for a country were applied to the distribution of age and sex in population of that country. If the country had no data, then the assumption was made that the sex and age specific diabetes mellitus prevalence rates were similar to the rates of another similar country that had the same geography, economy and ethnicity (39, 40).

3:- In low and middle income countries there were difference in diabetes prevalence rates for urban and rural populations. For that reason the prevalence rates for urban and rural areas were separately computed and reported in low and middle income countries. With an exception of countries which were classified as the former socialist or market economies by the WHO (39, 40).

To compute the prevalence of diabetes in a country where urban and rural prevalence rates were shown separately; the prevalence rates of urban area were applied to the total national urban

14

population of that country. Similarly the prevalence rates of rural areas were applied to the total national rural population of that country (39, 40).

Where there were mixed studies, and no separate data for urban and rural population were provided, then the gender and age specific available data was applied to the population to produce urban and rural ratio of 2:1 for diabetes prevalence (39, 40).

Where data for a country was available for only urban population or for only a rural population, then to compute the prevalence of diabetes in other population segments 2:1 was used (39, 40). For example if the data for only urban areas of a country was available then it was assumed that there is difference in the prevalence of diabetes of 2:1 between the urban and rural areas, respectively; to compute the prevalence in the rural area of that country.

For 2003 data, there was an exception for this 2:1 urban and rural prevalence respectively regarding India and Nepal, because the urban and rural ratio for the prevalence of diabetes was close to 4:1 in India and Nepal, as indicated by the cited data (39).

4:- For every country prevalence rate have been computed in two ways: (1) National or regional prevalence. (2) Comparative prevalence or age adjusted prevalence (40).

National or regional prevalence was taken for the year 2003, 2007 and 2010. For the year 2007 and 2010 comparative prevalence was also computed. Percentage of the population that has diabetes in each country or a region is shown by the national or regional prevalence. For evaluating diabetes burden for each country, national or regional prevalence is ideal. But by using national or regional prevalence, comparison between the countries and regions whose age structure is not similar cannot be done, because the prevalence of diabetes increases with age (40). For instance the national prevalence of diabetes in Japan was 7.2% and Samoa had the prevalence of 6.5%, in 2007. Here, the prevalence of diabetes in Japan appears to be higher, but we are not able to say that if this higher prevalence was due to the reason that Japan had older population or Japanese are more prone to have diabetes than Samoans (40). To compute comparative prevalence an assumption was made that every region and country has a same age profile; here the world population´s age profile has been used. This technique (age adjustment), removes the age difference between the countries and make the prevalence’s of two countries or regions comparable. For instance, the comparative prevalence of diabetes mellitus in the Samoans was computed to be 7.5%, and in Japan it was 4.9%, showing that the Samoans were more prone to diabetes than the Japanese, this is in contrast to the national or regional prevalence which shows Japanese to be more prone to diabetes. However, this prevalence cannot be used to evaluate the percentage of population with diabetes within a region or a country (40).

15

3.4.3. Data for Urban Living: Data for urban living is taken from the World Health Statistics 2010. Publications and databases are used to compile the World Health Statistics 2010. These databases are generated and maintained by regional offices and technical programs of the WHO (42). Estimations in the World Health Statistics 2010 are obtained from numerous sources which depend on each indicators availability and data quality. There are countries where health information and statistical systems are weak and the data is either not available or of inadequate quality. Adjustments were done to country reported data for its best use and for the correction of biases, to address missing values, and to increase the statistical comparability between the countries and over time. Modeling and statistical techniques were also used to fill up gaps in the data as well (42). 3.4.4. Data for Gross national income: Data for Gross national income per capita (PPP international Dollars) was also taken from World health statistics 2010.World health statistics has used World Bank atlas method for the categorization of countries. According to which countries with less than 996 international dollars(ID) were categorized as low income countries, between 996ID to 3945ID as lower middle income, 3946ID to 12195ID as upper middle income and countries which have 12196ID and above GNI were categorized as high income countries. Low and middle income countries are collectively called as developing countries and high income countries as developed countries. But the categorization based on income does not necessarily shows the actual development status of a particular country (43). 3.4.5. Data for percentage out of pocket health expenditure (% of private expenditure on health): Data for percentage out of pocket health expenditure was taken from World Bank website: www.worldbank.org. This variable represents any direct expense by the people to health practitioners, suppliers of medicines, appliances for therapy, and other goods and health services, who were intended primarily to contribute to restore or enhance the health of individuals or population (44).

16

3.5. Analysis 3.5.1. Descriptive analysis: Microsoft Excel 2007 and Microsoft Word 2007 were used to make tables and charts of:-

• Trend of sugar consumption from 2000 to 2007. • Trend of the prevalence of diabetes mellitus from 2003 to 2010. • Comparison of the prevalence of diabetes mellitus among the six WHO regions between

the year 2007 and 2010. • Comparison of the prevalence of diabetes mellitus within each WHO region between the

year 2007 and 2010. 3.5.2. Statistical analysis: STATA version 10 was used for the statistical analysis. Linear regression was performed to see the association and prediction of the dependent variable by the independent variables.

4. Results:

There were 49 countries out of 193 countries, which were not included in the analysis because data for all of the variables was not available for these countries. In African region data was missing for six countries in which two were developed and four were developing countries. In American region data was missing for four developing countries and one developed country.

In Eastern Mediterranean region data was missing for two developed and one developing country. In the case of Europe, data was not available for eighteen developed and two developing countries. In South East Asia data was missing for two developing countries, and finally in Western Pacific region data was not available for twelve developing countries.

17

4.1. Results for the trends of sugar consumption and diabetes mellitus.

Chart 1: Trend of the sugar consumption in the six WHO regions from 2000 to 2007.

‐ AFRO: African region. ‐ AMRO: American region. ‐ EMRO: Eastern Mediterranean region. ‐ EURO: European region. ‐ SEARO: South East Asian region. ‐ WPRO: Western Pacific region.

In chart 1, trend of sugar consumption per capita increases in five of the six WHO regions from

2000 to 2007. In the EURO, trend of sugar consumption is slightly decreased from year 2000 to

2007. The highest rise in sugar consumption per capita from year 2000 to 2007 is seen in the

EMRO from 28.5kg to 32.75kg with a difference of 4.25kg, followed by the WPRO from 25.8kg

to 29.37kg with a difference of 3.57kg, AFRO 15.65kg to 17.91kg with a difference of 2.26kg,

SEARO from 18.86kg to19.8kg with a difference of 0.94kg and in the AMRO from 41.013kg to

0

5

10

15

20

25

30

35

40

45

2000 2001 2002 2003 2004 2005 2006 2007

average sugar con

sumption in kilo

gram

s pe

r capita.

Year

AFRO

AMRO

EMRO

EURO

SEARO

WPRO

18

41.077kg with a difference of 0.064kg. In the EURO a slight decrease is seen from 36.60 kg

to36.47 kg with a difference of 0.13 kg.

Chart 2: Trend of the prevalence of diabetes mellitus among 20 to 79 years old in the six WHO regions during 2003, 2007 and 2010. (National prevalence).

‐ AFRO: African region. ‐ AMRO: American region. ‐ EMRO: Eastern Mediterranean region. ‐ EURO: European region. ‐ SEARO: South East Asian region. ‐ WPRO: Western Pacific region.

In chart 2, trend of the prevalence diabetes mellitus increases in all of the six WHO regions from

2003 to 2010.In the EURO, trend is increased from 2003 to 2007 and then decreased till 2010.

The highest rise in the prevalence of diabetes mellitus from year 2003 to 2010 is seen in the

SEARO from 3.43 % to 6.25%with a difference of 2.82 percentage points (pp), followed by the

AMRO from 6.76% to 8.21% with a difference of 1.45 pp, WPRO 5.73% to 6.95% with a

0

1

2

3

4

5

6

7

8

9

2003 2007 2010

Diabe

tes mellitus prevalence pe

rcen

tage

AFRO

AMRO

EMRO

EURO

SEARO

WPRO

19

difference of 1.22 pp, AFRO 2.6% to 3.63% with a difference of 1.03 pp, EURO 7.5% to 7.96%

with a difference of 0.46 pp and in the EMRO from 7.5% to7.77% with a difference of 0.27 pp.

Chart 3: Sugar consumption in 2001 and the prevalence of diabetes mellitus in 2010, in the six WHO

regions.

‐ DMC2010: Comparative prevalence percentage of diabetes mellitus in 2010.

‐ SC2001: Sugar consumption in kilograms per capita in 2001.

‐ Region 1 (blue dots): represent countries of African region (AFRO).

‐ Region 2 (green dots): represent countries of American region (AMRO).

‐ Region 3 (white dots): represents countries of Eastern Mediterranean region (EMRO).

‐ Region 4 (purple dots): represents countries of European region (EURO).

‐ Region 5 (yellow dots): represents countries of South East Asian region (SEARO).

‐ Region 6(red dots): represents countries of Western Pacific region (WPRO).

20

Most of the countries of AFRO (blue dots) have prevalence of diabetes mellitus within the range

of zero to five percent and sugar consumption in the range of zero to forty kilograms per capita.

Countries of AMRO (green dots) have prevalence of diabetes mellitus within the range of five to

twelve percent and have sugar consumption between eighteen to sixty two kilograms per capita.

Countries of EMRO have prevalence of diabetes mellitus between three to eighteen percent

while having sugar consumption between eighteen to forty two kilograms per capita.

Purple dots which represent countries from EURO have prevalence of diabetes mellitus within

the range of five to ten percent and have sugar consumption between five to sixty kilograms per

capita. Countries of SEARO are in yellow color which have prevalence of diabetes mellitus

between three to eleven percent and have sugar consumption in the range of two to thirty

kilograms per capita. Finally, the red dots represent countries of WPRO which have prevalence

of diabetes mellitus within the range of two to thirteen percent and have sugar consumption

between two to seventy kilograms per capita. This chart illustrates that, in countries where the

sugar was consumed more in 2001 had the higher prevalence of diabetes in 2010 than the

countries which had less sugar consumption, with exception of few countries.

4.2. Results for the comparison of diabetes mellitus prevalence between the year 2007 and 2010 in the six WHO regions.

0

1

2

3

4

5

6

7

8

9

10

11

AFRO AMRO EMRO EURO SEARO WPRO

dm07com

dm10com

21

Chart 4: Average diabetes mellitus prevalence among 20 to 79 years old in the six WHO regions during 2007 and 2010. (Age adjusted prevalence).

‐ dm07com: age adjusted diabetes mellitus prevalence percentage in 2007. ‐ dm10com: age adjusted diabetes mellitus prevalence percentage in 2010.

Chart 3 shows the comparison of average diabetes mellitus prevalence percentage between

regions during 2007 and 2010, using age adjusted prevalence. In the African region, the

prevalence of diabetes mellitus increased from 3.92% in 2007 to 4.24% in 2010, in the American

region from 8.2% to 8.45%, in the Eastern Mediterranean region from 9.21% to 9.71%, in the

South East Asian region it increased from 5.47% to 6.33% and in the Western Pacific region

from 6.46 %to 6.78%. Only in the European region the prevalence of diabetes is decreased from

6.78% in 2007 to 6.68% in 2010.

Among the six WHO regions, the EMRO has the highest prevalence of diabetes mellitus of

9.71% in 2010, then in the AMRO with prevalence of 8.45%, WPRO 6.85%, EURO 6.68%,

SEARO 6.23% and AFRO 4.24%, respectively. The highest change in the prevalence of diabetes

mellitus is seen in the SEARO of 0 .79 pp, secondly in the EMRO of 0.5 pp, then in the AFRO of

0.311 pp, WPRO 0.286 pp and in the AMRO of 0.25 pp. While in the EURO decrease of 0.1 pp is

seen.

4.3. Results for the comparison of diabetes mellitus prevalence between the year 2007 and 2010 within each of the six WHO regions.

22

Chart 5: Diabetes mellitus prevalence among 20 to 79 years old in the AFRO during 2007 and 2010. (Age adjusted prevalence).

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

AngolaBenin

BotswanaBurkina Faso

BurundiCameroonCape Verde

Central African RepChad

ComorosCongo rep

Cote d´IvoireEritrea

EthiopiaGabonGambiaGhanaGuinea

Guinea ‐ BissanKenyaLiberia

MadagascarMalawi

MaliMauritaniaMauritius

MozambiqueNamibia

NigerNigeriaRwandaSenegal

Sierra LeoneSouth AfricaSwaziland

Tanzania, United Rep ofTogo

UgandaZambia

Zimbabwe

DMC2010

DMC2007

23

‐ DMC2007: age adjusted diabetes mellitus prevalence percentage in 2007. ‐ DMC2010: age adjusted diabetes mellitus prevalence percentage in 2010.

In chart 4, every country shows an increase in the prevalence of diabetes mellitus, with a change in prevalence of 5.1 pp is seen in the Mauritius from the year 2007 to 2010.

Chart 6: Diabetes mellitus prevalence among 20 to 79 years old in the AMRO during the 2007 and 2010. (Age adjusted prevalence).

0 1 2 3 4 5 6 7 8 9 10 11 12 13

ArgentinaBahamasBarbados

BelizeBermuda

BoliviaBrazil

CanadaChile

ColombiaCosta Rica

CubaDominican rep

EcuadorEl SalvadorGutemalaGuyana

HaitiHonduras

JamicaMexico

NicaraguaPanama

PeruSt Kitts and Nevis

SurinameTrinidad and Tobago

UruguayUSA

VenezuelaParaguay

DMC2010

DMC2007

24


In chart 5, almost every country shows an increase in the prevalence of diabetes mellitus from 2007 to 2010, with a change seen in the USA of 2.5 pp, Canada 1.8 pp and in Venezuela of 1.1 pp. No change in the prevalence is seen in the Honduras, Guatemala, El Salvador and Costa Rica in this time period. Some of the countries which have shown decrease in the prevalence are Panama, Nicaragua and most prominently Haiti with a decrease of 1.8 pp.

Chart 7: Diabetes mellitus prevalence among 20 to 79 years old in the EMRO during 2007 and 2010. (Age adjusted prevalence).


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Afghanistan

Iran

Iraq

Jordan

Kuwait

Lebanon

Libiyan Arab J

Morrocco

Pakistan

Saudi Arabia

Sudan

Syrian Arab rep

Tunisia

Yemen

UAE

Djibouti

Egypt

DMC2010

DMC2007

25

In chart 6, nearly every country has shown increase in the prevalence of diabetes mellitus with a

marked change is seen in the Tunisia of 4.1 pp and in the Libyan Arab Jamahiriya of 4.6 pp,

while UAE, Pakistan and Afghanistan have shown decreasing trend.

Chart 8: Diabetes mellitus prevalence among 20 to 79 years old in the EURO during 2007 and 2010. (Age adjusted prevalence).


0 1 2 3 4 5 6 7 8 9 10

AlbaniaAzerbaijan

BelarusBosnia and herzegovina

BulgariaCroatiaCyprus

Czech RepublicEstoniaFranceGeorgiaHungaryIcelandIsrael

KazakhstanKyrgyzstan

LatviaLithuania

Macedonia former Yugoslavia repMalta

Moldova republic ofNorwayPoland

RomaniaRussian Federation

SlovakiaSlovenia

SwitzerlandTajikistan

TurkeyTurKmenistan

Ukraine

DMC2010

DMC2007

26

In chart 7, out of 35 countries 12 countries shows an increasing trend of diabetes mellitus

prevalence with a an increase in the Switzerland of 1 pp is seen from 2007 to 2010, 10 countries

have shown no change and 9 countries have shown decreasing trend. Slovakia, Hungary and

Czech Republic has shown 1.2 pp decrease in the prevalence while the Bulgaria has shown 1.1 pp

decrease.

Chart 9: Diabetes mellitus prevalence among 20 to 79 years old in the SEARO during 2007 and 2010. (Age adjusted prevalence).


In chart 8, most of the countries have shown increase in the prevalence of diabetes mellitus with

a marked increase seen in the Sri Lanka of 2.5 pp, Indonesia 2.5 pp, India 1.1 pp and Bangladesh

1.3 pp. No change is seen in the prevalence of diabetes mellitus in the Myanmar while decrease

in prevalence is seen in the Nepal.

0 1 2 3 4 5 6 7 8 9 10 11 12

Bangladesh

India

Indonesia

Korea,democratic rep of

Maldives

Myanmar

Nepal

Sri Lanka

Thailand

DMC2010

DMC2007

27

Chart 10: Diabetes mellitus prevalence among 20 to 79 years old in the WPRO during 2007 and 2010. (Age adjusted prevalence).


In chart 9, out of 15 countries 13 have shown increase in the prevalence of diabetes mellitus

especially in the Lao People Democratic Republic where the increase is of 2.5 pp. Decrease in

diabetes mellitus prevalence is seen in the New Zealand and Mongolia.

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Australia

Brunei

China

Fiji

Japan

Korea rep of

Lao PDR

Macau

Malaysia

Mongolia

New Zealand

Papua new Guinea

Philippines

Singapore

Viet Nam

DMC2010

DMC2007

28

4.4. Results for the analysis of association between sugar consumption and the diabetes mellitus prevalence in the 144 WHO member state and within each WHO region.

To analyze the association between the prevalence of diabetes mellitus with sugar consumption, urbanization and percentage out of pocket payment a linear regression was performed. Predictions were also made to show changes in the prevalence of diabetes mellitus as sugar consumption, urbanization and out of pocket payment increases.

Table 2: Linear regression analysis, to observe the association between the sugar consumption, urbanization and out of pocket payment with the diabetes mellitus prevalence in the 144 WHO member states, using STATA 10.

‐ dm10com: diabetes mellitus in 2010. ‐ sc01: Sugar consumption in 2001. ‐ ul00: Urban living percentage in 2000. ‐ opp: Percentage Out of pocket payment in 2009.

Interpretation of table 2:

With one kilogram increase in sugar consumption, the diabetes mellitus prevalence percent will

increase by 0.0628, when the urban living percentage and percentage out of pocket payment is

kept constant. The result is statistically significant, because the P-value is less than 0.05, that is,

0.000 and 95% confidence interval does not include 0.

Region All 6 WHO regions

Coefficient(B) P‐value

95% Confidence interval

dm10com

sc01 0.0628906 0.000 0.0342702 0 .091511

ul00 0 .029716 0.012 0.0067083 0.0527238

Opp 0.0033646 0.747 ‐0.0171894 0.0239186

29

With one percent increase in the urban living, the diabetes mellitus prevalence percent will

increase by 0.029, when the sugar consumption and percentage out of pocket payment is kept

constant. The result is statistically significant because the P-value is less than 0.05, that is, 0.012

and 95% confidence interval does not include 0.

With one percent increase in out of pocket payment, the diabetes mellitus prevalence percent

will increase by 0.0033, when the sugar consumption and urban living percentage is kept

constant. The result is statistically insignificant because the P-value is greater than 0.05, that is,

0.747 and 95% confidence interval includes 0.

Table 3: Linear regression analysis, to observe the association of sugar consumption, urbanization and out of pocket payment with the diabetes mellitus prevalence within the AFRO, AMRO and EMRO, using STATA 10.


Interpretations of table 3:

(1)For one kilogram increase in the sugar consumption in the AFRO, the diabetes mellitus prevalence percent will increase by 0.032, when the urban living percentage and percentage out

Region AFRO P ‐VALUE

AMRO P ‐VALUE

EMRO P‐ VALUE

Coefficient(B) Coefficient(B) Coefficient(B)

dmc10

sc01 0.0323727 0.075 0.0642228 0.072 0.0526805 0.510

ul00 0.0471322 0.030 ‐0.0378233 0.073 0.0346272 0.409

opp09 0.0160805 0.243 ‐0.0153386 0.422 ‐0.1727879 0.016

30

of pocket payment is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.75.

With one percent increase in the urban living, the diabetes mellitus prevalence percent will increase by 0.047, when the sugar consumption and percentage out of pocket payment is kept constant. The result is significant because the P value is lesser than 0.05, that is, 0.03.

With one percent increase in out of pocket payment, the diabetes mellitus prevalence percent will increase by 0.016, when the sugar consumption and urban living percentage is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.243.

(2)For one kilogram increase in the sugar consumption in the AMRO, the diabetes mellitus prevalence percent will increase by 0.064, when the urban living percentage and percentage out of pocket payment is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.72.

With one percent increase in the urban living, the diabetes mellitus prevalence percent will decrease by 0.037, when the sugar consumption and percentage out of pocket payment is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.073.

With one percent increase in out of pocket payment, the diabetes mellitus prevalence percent will decrease by 0.015, when the sugar consumption and urban living percentage is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.422.

(3) For one kilogram increase in the sugar consumption in the EMRO, the diabetes mellitus prevalence percent will increase by 0.052, when the urban living percentage and percentage out of pocket payment is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.510.

With one percent increase in the urban living, the diabetes mellitus prevalence percent will increase by 0.034, when the sugar consumption and percentage out of pocket payment is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.409.

With one percent increase in out of pocket payment, the diabetes mellitus prevalence percent will decrease by 0.1727, when the sugar consumption and urban living percentage is kept constant. The result is significant because the P value is lesser than 0.05, that is, 0.016.

31

Table 4: Linear regression analysis, to observe the association of the sugar consumption, urbanization and out of pocket payment with the diabetes mellitus prevalence within the EURO, SEARO AND WPRO, using STATA10.


Interpretations of table 4:

(4) For one kilogram increase in the sugar consumption in the EURO, the diabetes mellitus prevalence percent will increase by 0.059, when the urban living percentage and percentage out of pocket payment is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.071.



(5) For one kilogram increase in the sugar consumption in the SEARO, the diabetes mellitus prevalence percent will increase by 0.192, when the urban living percentage and percentage out

REGION EURO P ‐VALUE

SEARO P ‐VALUE

WPRO P‐ VALUE

Coefficient(B)

dmc10

sc01 0.0594804 0.071 0.1924266 0.026 0.0957398 0.114

ul00 ‐0.0359348 0.145 ‐0.0128991 0.776 ‐0.0045424 0.928

opp09 ‐0.0234755 0.190 0.0841723 0.239 ‐0.0585176 0.087

32

of pocket payment is kept constant. The result is significant because the P value is lesser than 0.05, that is, 0.026.


With one percent increase in out of pocket payment, the diabetes mellitus prevalence percent will increase by 0.084, when the sugar consumption and urban living percentage is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.239.

(6) For one kilogram increase in the sugar consumption in the WPRO, the diabetes mellitus prevalence percent will increase by 0.095, when the urban living percentage and percentage out of pocket payment is kept constant. The result is insignificant because the P value is greater than 0.05, that is, 0.114.



In table 3, the results for the association of sugar consumption and the prevalence of diabetes mellitus were insignificant, for all the three WHO regions. While in table 4, the results for the association of sugar consumption and the prevalence of diabetes mellitus were significant for the SEARO region, but insignificant for the other 2 regions.

For the association between urbanization and the prevalence of diabetes mellitus, in table 3, the result is significant for AFRO but insignificant for other two regions. While in table 4, the results are insignificant for the association between urbanization and the prevalence of diabetes mellitus, for all the three regions.

For the association between percentage out of pocket payment and the prevalence of diabetes mellitus, in table 3, the result is significant for EMRO region while insignificant for other two regions. In table 4, the results are insignificant for all the three regions.

These insignificant results at regional level are probably due to fewer observations within each region, that is, a power problem.

33

5. Discussion:

This study demonstrated that, increased sugar consumption is positively associated with the prevalence of diabetes mellitus. The analysis of this study revealed that, with an increase in sugar consumption per capita the prevalence of diabetes mellitus increases, after controlling for confounders (table 2, 3, 4). The findings of this study are in accordance with other studies, which have shown similar results of association between sugar consumption and diabetes (2, 19, 20, 21, 22, 23, 24, 25).

Some of the studies have used soft drinks as a proxy for sugar consumption. The results of these studies have shown positive association of increased risk of type 2 diabetes mellitus with consumption of soft drinks. In soft drinks, sugar is added as a flavor (2, 19, 20, 21, 22).

Confounders such as obesity and physical activity were also considered in this study. But these independent variables were not included separately in analysis. The reason for that is the available data on these variables cannot be compared.

There were some inconsistencies with the available data for obesity and physical activity, for example, for some countries it is available for different age groups, while for some countries it is available without any age group differentiation. There is also substantial difference between years in which data is collected for different countries. For some countries data is available for different gender, that is, for some countries it is available for both, males and females, and for some countries it is available for either males or either females.

In this study, urbanization was used as a proxy for the risk factors which are associated with diabetes mellitus. Urbanization is associated with lifestyle changes, which exposes individuals to various risk factors that can lead to non communicable diseases (36, 40). These risk factors are, increase use of junk food, obesity and physical inactivity. There are many studies that have shown the increased risk of diabetes mellitus in people who are living in urban areas as compare to people in rural areas (37, 38, 39, 40).

This study has shown positive correlation of urbanization with the prevalence of diabetes mellitus, at global level. Initially linear regression was performed to observe the association of the prevalence of diabetes mellitus with sugar consumption, urbanization, out of pocket payment and GNI per capita (gross national income). Later on, the variable GNI was dropped from the data, because of its high correlation with urbanization.

The reason to use GNI as a separate variable is that the increasing sugar consumption might be associated with increasing income of the people. As with increasing income, people can have more access to sweet products. Variable GNI was dropped from this study because of its high correlation with urbanization, which illustrates that, as the people are becoming more urbanized their income is increasing, which in turn can increase their access to sweet products.

In the case of diabetes mellitus prevalence, out of 4.3 billion people in the world among age group of 20-79 years, 6.4% or 285 million people have diabetes. This figure will rise by 7.7% or 438 millions in 2030, as population size grows (13). In this study, out of the selected 144 WHO

34

member states, 110 countries have shown increase in the prevalence of diabetes mellitus, 18 countries have shown decrease, and 11 countries have shown no change, between 2007 and 2010.

The results of this study shows, increasing trend in both, sugar consumption per capita and the prevalence of diabetes mellitus, in five of the WHO regions. This shows a possibility of an increase in the prevalence of diabetes mellitus when there is an increase in sugar consumption. Conversely, in the case of Europe, where as the trend of sugar consumption per capita decreases, the trend of the prevalence of diabetes mellitus also decreases.

In the result section association between dependent and independent variable was shown for different regions separately. In this study, linear regression was also performed which included all regions as independent variables (dummy variables), instead for each region separately. The analysis in which dummy variables for regions were included as independent variables further weaken the association between dependent and independent variables, as compared to analysis without the dummy variables.

In this study, percentage out of pocket health expenditure was also included as an independent variable as a proxy for health system coverage in every country, to observe whether the good health coverage can improve the reported prevalence of diabetes mellitus. If this is the case then out of pocket health expenditure should weaken the association between sugar consumption and prevalence of diabetes mellitus. However, results have shown that this variable strengthens the association between sugar consumption and diabetes mellitus, but the result was insignificant.

This study shows a positive association between the prevalence of diabetes mellitus with sugar consumption and urbanization, at a global and regional level. Though, because of the use of aggregate data, this study is subjected to an ecological fallacy. That is, this study does not show association at an individual level.

However, even if the intended level of inference is at individual level, an ecological study is also of particular importance, because the intervention for prevention of diabetes mellitus can be applied at population level. For example, rules and regulations can be implemented on the soft drink manufacturers, to reduce sugar content in their products. Many studies have demonstrated that, sugar sweetened beverages are correlated with increased risk of diabetes mellitus (2, 19, 20, 21, 22).

There are 49 countries out of 193 countries which are not included in this study because data was not available for all the variables for these countries. This can also affect the results of this study. For example, these countries may have less prevalence of diabetes mellitus while having high level of sugar consumption or they may have high prevalence of diabetes mellitus while having low level of sugar consumption.

For the prevalence of diabetes mellitus, there were some limitations mentioned by the IDA such as, different techniques for the screening of diabetes mellitus were used. Most of the countries have used OGTT as a screening method. But some of them have used only one method for the

35

screening of diabetes mellitus, which includes, fasting blood glucose, two hour blood glucose, random blood sampling and self report.

To control this difference of the screening methods, studies which used OGTT as a screening method were included. But because of this, there was an effect of exclusion of countries without an OGTT data, because for these countries data was extrapolated from another similar country. For the countries that have no data, it was presumed that the age as well as sex specific diabetes mellitus prevalence rate of that country is same as of similar country, in respect of socio economy, geography and ethnicity.

There were also some inconsistencies in adopting diagnostic criteria which was resulted from the updating of diagnostic criteria, i.e. some countries have used lower fasting diagnostic criteria, which resulted in the higher diabetes mellitus prevalence in that country. Few of the countries may not represent current rates of the diabetes mellitus prevalence because they are over a decade old. Prevalence estimated by these studies is possibly a conservative approximation.

This study has considered refined or centrifuged sugar but it does not include data for other types of sugars such as fructose corn syrups and other raw sugars. Refined sugar is the most commonly used sugar in the world which is used in the preparation of confectionary products and soft drinks; for example, giant soft drink manufacturers like Pepsi, Coca cola, Doctor Pepper and several others are using refined sugar. However, data for only refined sugar is a limitation in this study.

For sugar consumption, some of the countries have reported figures of sugar consumption in metric tons. But for some countries, data was estimated on the basis of countries imports and exports of sugar, and the data on imported confectionary products was also not considered. This may not represent actual figures of sugar consumption in those countries.

Countries who have reported sugar consumption in metric tons may be based on the total sale of sugar in those countries. If this is the case then the figures for sugar consumption can be misleading. The reason for that is, sugar can also be utilized in other manners rather than its intake only, for e.g., in the production of ethanol.

6. Recommendations:

1) Use of sugar should be reduced in diet and rule and regulations should be made to limit the use of sugars, especially in soft drinks, which offer readily absorbable sugar together with other sugar rich food products. This can act effectively as a public health strategy.

2) Studies should be performed to extract proper up to date data on sugar consumption and its association with diabetes, as data on this topic is scarce.

36

3) To tackle the issue of this global burden of diabetes there is a need of global action plan for its prevention.

7. Conclusion:

The prevalence of diabetes mellitus appeared to be increasing with time which was apparently linked to modifiable risk factors, such as sugar intake. Diabetes prevalence was also associated with urbanization, which was used as a proxy for various risk factors, such as increased consumption of junk food, obesity and physical inactivity. There is a need to address this issue on the global level, because the impact of this non communicable chronic disease is substantial, and together with its complications, it will result in disability and premature deaths around the world. This global burden of diabetes is in turn hampering the economic growth and stability, throughout the world.

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