Walter Sisulu University

PROFESSORIAL INAUGURAL LECTURE 22 MAY 2013 15H00 MTHATHA HEALTH RESOURCE CENTRE

Topic: The emerging epidemic of diabetes mellitus: a 20 year community study in former Transkei

Professor EV Blanco-Blanco Professor of Chemical Pathology Faculty of Health Sciences Walter Sisulu University Eastern Cape South Africa

Auditorium, Mthatha Health Resource Centre, Mthatha, Eastern Cape

www.wsu.ac.za

WALTER SISULU UNIVERSITY (WSU) DEPARTMENT OF CHEMICAL PATHOLOGY SCHOOL OF MEDICINE FACULTY OF HEALTH SCIENCES

TOPIC “THE EMERGING EPIDEMIC OF DIABETES MELLITUS: A 20-YEAR COMMUNITY STUDY IN THE FORMER TRANSKEI”

BY ERNESTO V. BLANCO-BLANCO PROFESSOR OF CHEMICAL PATHOLOGY

DATE: 22 MAY 2013

VENUE: UMTATA HEALTH RESOURCE CENTRE

3 4 INTRODUCTION AND TOPIC MOTIVATION

DIABETES MELLITUS Definition Historical background CLASSIFICATION OF DIABETES MELLITUS DIAGNOSIS OF DIABETES MELLITUS

RISK FACTORS AND PREDISPOSING CONDITIONS FOR DIABETES COMPLICATIONS OF DIABETES MELLITUS

THE GLOBAL PREVALENCE & GLOBAL BURDEN OF DIABETES

THE AFRICAN BURDEN OF DIABETES MELLITUS

THE SOUTH AFRICAN BURDEN OF DIABETES MELLITUS

CONSEQUENCES OF THE BURDEN OF DIABETES

IMPLICATIONS OF THE BURDEN OF DIABETES FOR HEALTH PLANNING DIABETES PREVENTION AS STRATEGY CONTROL OF THE CURRENT BURDEN OF DIABETES

CONCLUSIONS

REFERENCES

5 INTRODUCTION AND TOPIC MOTIVATION

Chemical Pathology, Diabetes Mellitus and the Former Transkei

I am a Chemical Pathologist by training. The term ‘pathology’ derives from the Greek words “pathos” meaning “disease” and “logos” meaning “a treatise”. Pathology is a major field of Medicine that deals with the essential nature of diseases, their processes and consequences. A medical doctor that specializes in pathology is known as ‘a pathologist’. Chemical Pathology is that branch of Pathology, which deals specially with the biochemical basis of diseases and the use of biochemical tests carried out at hospital laboratories on the blood and other body fluids to provide support to clinicians. It does this in the following processes: Screening: identifying an unrecognised disease in individuals without signs or symptoms Diagnosis: identifying the nature and cause of a disease Prognosis: predicting the probable outcome or course of a disease Management: implementing health interventions to deal with a disease

Along these lines, chemical pathologists have two main clinical roles. The first one is to collaborate with healthcare professionals such as clinicians and nurses, to advise them on how to choose the tests and how to interpret their results when investigating a case. The second role is a personal responsibility for patients in outpatient clinics and on the hospital wards, which entails validation and interpretation of test results, mostly for peculiarly surprising results and for infrequent or highly specialised tests. In addition, the roles of an academic pathologist include devising and conducting scientific research and training healthcare personnel.

Chemical pathology investigations are of value, to different extents, in recognition of most diseases. However, the importance and relevance is essential in those conditions in which biochemical derangements constitute the essential nature of the disease; for example, hepatic, renal and endocrine diseases such diabetes mellitus. Diabetes is a common chronic disease worldwide that starts as an abnormal blood glucose level associated with a series of related biochemical abnormalities. In addition, a whole assortment of biochemical investigations provides evidence for a wide range of severe acute and long-term diabetic complications. Abnormal tests results from diabetic patients, are not only frequent but also, quite commonly, are serious enough to require attention by the chemical pathologists in conjunction with clinical staff.

Under the above circumstances, the subject of “diabetes mellitus” has also attracted my interest as a researcher with the subsequent engagement in some interdepartmental collaborative research projects on diabetes. These are the reasons informing my choice of diabetes mellitus as a topic for this presentation. Lastly, due to my many years of affiliation to the University of Transkei, legacy institution of the Walter Sisulu University, and, in consonance with the principle of community relevance of this academic institution, most of our research on diabetes mellitus has addressed epidemiological issues. The goal has been to contribute to develop the knowledge and understanding of the epidemiological patterns, clinical and biochemical peculiarities inherent to diabetes mellitus in the community of the former Transkei; a largely rural and historically disadvantaged population sector of the Eastern Cape, predominantly constituted by black South Africans of Xhosa ethnic origin. Those are the reasons for combining the topic of diabetes with the community of the former Transkei.

In spite of the advances in the medico-pharmaceutical field, and the efforts made by governments and non-governmental organizations, the prevalence of diabetes mellitus has been increasing worldwide

6 at an alarming rate in the last few decades. The geographic pattern of this epidemic across the globe is quite uneven. However, some significant differences recently identified embody the distinctive characteristics of the different continents, regions, countries, provinces and communities.

Understanding the reasons behind this epidemic is essential for the identification of specific and effective strategic actions required. Combinations of different factors contribute to the global burden of diabetes. Although this multi-factorial influence is in general, not arguable, it is widely accepted that the geographic differences observed result from the varying degrees of intensity of each of its regulatory factors. Thus, it is not likely that a single strategy could be a practical solution of the global problem. A locally relevant approach is required for each different area. The first step in this process is the delimitation of the differences and commonalities between adjacent areas or coexisting populations.

This lecture intends to raise awareness on the current global epidemic of diabetes mellitus, its increasing prevalence and growing burden, as well as its socio-economic and healthcare impact. It also intended to describe the pattern of diabetes observed in the community of the former Transkei. It is also the intention to highlight possible collaborative areas to counteract the increasing burden of diabetes in South Africa and more specifically in the community around WSU.

DIABETES MELLITUS

Definition

According to the World Health Organization (WHO), “diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycaemia with disturbances of carbohydrate, fat and protein metabolism resulting from defects in insulin secretion, insulin action, or both” (World Health Organization 1999).

Historical background There are evidences that diabetes mellitus, as a disease, has been described since around 1500 B.C. in the ancient Egypt as a condition associated with excessive urination and loss of weight. Although most civilizations have in some way referred to the disease, it was the Greek physician Aretaeus around the 80 to 138 B.C., who introduced for the first time the term “diabetes”, whilst later; in the 18th century; the Scottish physician John Rollo introduced the adjective “mellitus” to reflect the “honeyed” aspect of the diabetics’ urine. It was only in 1776 that Matthew Dobson identified the increased level of glucose in the urine of diabetics and almost 150 years later a group of scientists discovered the insulin, a pancreatic hormone controlling the blood glucose. Since then, the perception and management of diabetes mellitus has changed dramatically as well as the life expectancy of diabetic patients. An important number of other scientists have continued the arduous work in the last century contributing to the current knowledge on this condition (Holt, Cockram 2010; Flyvbjerg & Goldstein, 2010, Chapter 1, p. 3-9).

Diabetes mellitus belongs to the group of non-communicable diseases (NCDs). This category includes non-infectious conditions characterized by long duration and a generally slow progression. Appart from diabetes the other three most common non-communicable diseases currently affecting the world are cardiovascular diseases (such as heart attack and stroke); cancers, and chronic respiratory diseases (such as chronic obstructed pulmonary disease, asthma).

Non-communicable diseases are largely more frequent in the low- and middle-income countries where nearly 80% of NCD worldwide deaths occur. They are the leading causes of death in all regions

7 except Africa, where common causes of death are those related to communicable (infectious) and nutritional diseases together with maternal and foetal deaths. However, projected estimates suggest that, by 2030, the mortality attributable to NCDs in Africa, will most likely exceed the current leading causes of death (World Health Organization 2011).

CLASSIFICATION OF DIABETES MELLITUS

According to the classification by the American Diabetes Association (2013a) and the World Health Organization (Expert Committee on the Diagnosis and Classification of Diabetes Mellitus, 2003) four main types of diabetes mellitus are recognized, namely:

Type 1 DM, previously known as juvenile or insulin dependent DM (IDDM), which usually presents before the age of 35 years. This type, although more clinically devastating, accounts only for about 5% to 10% of the global number of diabetics. It is associated with strong genetic predisposition to the autoimmune destruction of the pancreatic beta cells. The progression of the beta cell destruction, which is usually more rapid for infants and children than for adults, results in insufficient insulin production by the endocrine pancreas. The deficiency of insulin makes these diabetics prone to ketoacidosis thus; becoming dependent on insulin therapy to survive.

Type 2 DM, previously named as diabetes of the adult or non-insulin dependent DM (NIDDM), which presents commonly in subjects older than 35 years. This type is frequently associated with obesity, mostly of the central type (abdominal). The disease mechanism is related to deficient insulin action (or “insulin resistance”), rather than to the insulin amount. Initially the hyperglycaemia is not so severe, thus, asymptomatic. It often remains undiagnosed for many years, progressing gradually, until becoming clinically overt. Ketoacidosis is not common with this type. Although, this type is sometimes treated with insulin, these patients usually respond to oral drugs that enhance the insulin action. Type 2 DM accounts for the vast majority of cases worldwide being the one responsible for the current global diabetes epidemic.

Other specific types: these are relatively rare and usually associated with specific genetic or endocrine conditions. The mechanism of disease entails a variety of complex processes such as endocrine dysregulations usually not primarily pancreatic, genetic defects related to the pancreatic beta cells or to the insulin action. Others are due to diseases of the exocrine pancreas, chemicals, and to some viral infections.

Gestational DM: includes different degrees of glucose intolerance, which appear for the first time during pregnancy. The mechanism of the disease involves some complex endocrine changes associated with pregnancy.

The main advantage of using a classification, in the medical context, is to separate groups that share common mechanisms, clinical presentations, investigations and thus a common therapeutic approach. Therefore, it is not surprising that when a subgroup, within a specific type, requires specific variation of the traditional therapeutic approach, it is identified as a subtype. Some subtypes of type 1 and type 2 DM have also been described to highlight their need for special therapeutic approach at least under certain circumstances (American Diabetes Association 2013a; Balasubramanyam et al 2008).

8 DIAGNOSIS OF DIABETES MELLITUS

Although there is a classical combination of clinical signs and symptoms usually accompanying hyperglycaemia such as polyuria, polydipsia, weight loss, sometimes with polyphagia, and blurred vision the clinical presentation lacks sensitivity and specificity for the confirmation of diabetes mellitus. Therefore, the diagnosis of DM has been set to specific “biochemical criteria” based on the levels of blood glucose in either the fasting state or 2 hours after the oral administration of a standardized glucose load (glucose tolerance test).

(National Diabetes Data Group, 1979; Expert Committee on the Diagnosis and Classification of Diabetes Mellitus 1997)

In the last few decades, the biochemical criteria for diagnosing DM have been revised and modified as a consequence of new concrete evidences regarding the expression of the disease and its complications in relation to the level of hyperglycaemia. Table 1 shows a summary of those changes as published by Herman et al (2005).

Table 1: Comparison of the different biochemical criteria for diagnosis of diabetes mellitus in the last five decades

Fajans and Conn USPHS NDDG WHO ADA (1954)(ref.1) (1964)(ref.11) (1979)(ref.3) (1980/1985)(ref.27) (1997)(ref.4) Glucose dose 1.75g/kg IBW* 100g 75g 75g 75g Fasting - 125 140 140 127 30 min - - 200 - - 60 min 185 195 200 - - 90 min 160 - 200 - - 120 min 140 140 200 - 200 180 min - 125 - 200 - Criteria for All three At least three Fasting or 120min Fasting or 120min Fasting or 120min positive test and intermediate

ADA, American Diabetes Association, NDDG National Diabetes Data Group, USPHS Us Public Health Service, WHO World Health Organization, IBW ideal body weight from Metropolitan Life Insurance Tables Changes in diagnostic criteria along the years have also brought some implications to the total prevalence of diabetes mellitus reported in the independent research publications. Thus, it is established that to provide comparable prevalences at different points in time, the original data requires some adjustments to match the criteria used. Similar effects arise when different diagnostic criteria are used to obtain estimates of DM prevalence (Shaw et al 1999).

Currently there are two approaches to the biochemical diagnosis of DM. First, the American Diabetes Association (ADA) (American Diabetes Association 2013a) has agreed on using only the plasma glucose levels during a fasting state. On the other hand, the World Health Organization (WHO) accepts the same fasting plasma glucose criteria but recommends, in addition, the use of the level of plasma glucose in the second hour of the glucose tolerance test. This additional biochemical criterion increases the sensitivity of the biochemical diagnosis as some differences in the fasting and the post-load glucose values are commonly present in different populations. Thus, if the 2-hour plasma glucose is not measured, the patient’s glucose-regulation status is “uncertain” because diabetes or impaired glucose tolerance (IGT) cannot be excluded (World Health Organization 2006).

For both, the ADA and the WHO diagnostic recommendations, the cut-off values for diabetes are fasting plasma glucose ≥ 7.0mmol/L and the 2–hours OGTT plasma glucose ≥ 11.1 mmol/L. The clinical value of these biochemical criteria is only to confirm the diagnosis of diabetes. Thus, they apply uniformly to the diagnosis of type 1, type 2 and non-specific types of DM. In the case of “gestational diabetes mellitus” (GDM), due to the special implications of hyperglycaemia during 9 pregnancy, the biochemical criteria require higher sensitivity, therefore, the recommended levels are lower than for other types of diabetes (American Diabetes Association 2012).

Following biochemical diagnosis, the type of diabetes is identified depending on the evidence collected for each patient with respect to the family history of DM, the age at the onset, the presence of specific risk factors and the clinical course of the disease among others (World Health Organization 2006).

In terms of diagnosis, there are some fairly recent studies (ADA 2009; Nathan et al 2008) showing evidence in support of using the glycosylated Haemoglobin (HbA1c), a test that correlates with the long-term presence of hyperglycaemia, to confirm diabetes. Because of irregularities in technical standardization of the test, in 2011 the World Health Organization introduced it as a conditional recommendation. A cut off value of HbA1c > 6.5% is diagnostic of diabetes “providing that stringent quality assurance tests are in place, and assays are standardised to the international reference values, and there are no conditions present which preclude its accurate measurement”. However, a value of less than 6.5% does not exclude diabetes (World Health Organization 2011).

RISK FACTORS AND PREDISPOSING CONDITIONS FOR DIABETES

The risk factors for diabetes are related to the mechanism of disease, which are particularly different for each type of diabetes. In general, the risk factors are categorized under the two main groups of “modifiable” and “non-modifiable” according to the possibility of using interventions to control their expression.

RISK FACTORS FOR TYPE 1 DM

In the case of type 1 diabetes mellitus, the disease is associated with non-modifiable genetic and immunological factors. There is a genetic predisposition arising from the makeup of the HLA susceptibility loci, particularly for HLA-DR3, HLA DR4 and their combinations (Ekoe et al 2008; Osei et al 2003).

Some studies have reported additional details regarding allele-specific probes used in different populations from sub-Saharan Africa have found a positive association of diabetes with specific genetic markers such as the alleles DQB*0201, DQB*0302, DRB*0301, and DRB*0401 and negative association with DQB*0501 (Mbanya et al 2001). In addition, polymorphisms of the toll-like receptor 3 (TLR3), which is part of the innate immune system, has been reported in type 1 diabetics from South Africa by Pirie and co-workers (2005).

RISK FACTORS FOR TYPE 2 DM

The two categories of risk factors, modifiable and non-modifiable, are important for type 2 DM.

Non-modifiable risk factors

These include the age, the family history and the ethnicity. The widespread observation is that the risk of becoming diabetic increases progressively with the age reaching peak frequencies around the 65 years (Levitt 2008; International Diabetes Federation 2011). This association is responsible for the relatively steady high prevalence of diabetes in the developed countries where the older age group prevails in the population distribution (Elbagir et al 1996, 1998; Amoah, Owusu & Adjei 2002). Given this fact, it is also understandable that most new 10 cases in the projected prevalence of diabetes will emerge from the developing countries because of the ageing of the population inherent to socioeconomic development.

The association with a positive family history of diabetes supports the stronger genetic predisposition of type 2 diabetes although usually by mechanisms other than autoimmunity. The family history of diabetes has also been widely identified as an independent risk factor for this disease (Permut 1990, Hitman & McCarthy 1991, Klein et al 1996, American Diabetes Association 2013a). There is also evidence of its higher influence in African populations (Elbagir 1996 & 1998, Erasmus et al 2001a, Motala et al 2008) although according to Levitt et al (1993) this pattern has not been supported by studies in black South African urban communities.

Modifiable risk factors

Modifiable risk factors include adiposity, physical activity, diet, associated diseases, as well as urbanization and migration. Increased adiposity, expressed in the categories of overweight and obesity, is derived from anthropometric measurements. A commonly used indicator of adiposity is the Body Mass Index (BMI), which results from a mathematical calculation that combines the weight and the height of the person. Increased BMI and other indicators of increased adiposity such as the waist to hip ratio (WHR) and the waist circumference have been frequently observed in association with diabetes and other abnormal blood glucose states. Most studies have reported that the obesity of predominant central or abdominal distribution associates with higher risk of diabetes, as opposed to the protective role attributed to one predominant around hip circumference (Kissebah & Krakower 1994; Goedecke, Jennings & Lambert 2005).

Physical activity and the diet have also been attributed to some extent in increasing the risk of diabetes. Most published studies from Africa regarding physical activity do have limitations in the validity of the tool used for data collection. Two notable studies from Cameroon and Kenya based on standardized monitoring of physical activity in free-living persons have strongly supported the higher level of physical activity present in rural life and its beneficial effect on the glucose regulation (Christensen 2008; Assah 2009).

A review on the effect of the diet on the risk of DM published by Parillo & Riccardi (2004) found that the dietary pattern is commonly reportedreported influencing the risk of type 2 DM. Thus, a leading risk factor to be controlled is the diet and its effects on body weight. Most diabetes prevention programs have provided evidence of the benefits of changes in diet behaviour (Dehanty & Halford 1993; American Diabetes Association and National Institute of Diabetes, Digestive and Kidney Diseases 2002). Among the various recommended diet modifications, one of the most frequent is the reduction in type and total intake of fats. According to Storlien et al (1996) the high intake of fats is not only related to higher risk of weight gain, but it also induces increases of insulin sensitivity, which are, independent on changes in body weight. Several studies have also confirmed the role of saturated animal fat as a risk factor for type 2 diabetes, and the protective effect of the vegetable, unsaturated fats. (Laaksonen et al 2002; Wang et al 2003).

The typical western diet has been associated with obesity. The introduction of western-like diet commonly associated with urbanization have also been reported to be associated with higher risk of diabetes not only in the white and Indian community but also especially in the black African people (Loock et al 2006). In the African context, there is a shortage of evidence-based reports on physical activity and the nutritional assessment mostly due to the technical difficulties in obtaining validated measurements for their timelines under normal living conditions (World Health Organization 1990; Fung et al 2007). 11 However, in black South Africans records show of increasing consumption of fat and decreasing intake of carbohydrates in both the rural and urban settings. Associated effects of physical activity and urbanization are somehow moderating the influence exerted by the diet. Urbanization, a condition commonly associated with migration of people, results in an increased availability of fruits and vegetables improving the nutrient content of urban diets whilst it could also increase the intake of fats associated with the “westernization” of the diet (Bourne, Lambert & Steyn, 2002; Mennen et al 2001; Vorster et al 2005).

Some studies have provided evidence that the changes in dietary pattern associated with the urbanization of black South African communities also increase their susceptibility, not only to diabetes, but also cardiovascular diseases in general (Steyn et al 2005; Tibazarwa et al 2009).

Cultural influences related to increased risk for type 2 diabetes

In the African environment, the most common risk emerging from the cultural expressions is the misconception related to the popular belief that obesity reflects gracious living, which can also lead to the misperception that obesity is also a sign of excellent health (Goedecke, Jennings & Lambert 2005; Renzaho 2004).

Lastly, in terms of risks for diabetes, in the African context, there have been some reports supporting the association of antiretroviral therapy used for HIV/AIDS with some metabolic derangements including abnormal glucose regulation. The extent of this association as reported by different studies fluctuates between 2 and 14% (Friis et al 2003; Smith et al 2004; Glass et al 2006; Tien et al 2007).

Biochemical categories of increased risk for diabetes

In 1997 and 2003, the Expert Committee on Diagnosis and Classification of Diabetes Mellitus recognized an intermediate group of individuals whose glucose levels do not reach the criteria for diabetes although they are higher than those considered normal. These people have been defined as having impaired fasting glucose (IFG) [fasting plasma glucose (FPG) levels between 5.6 mmol/L and 6.9 mmol/L, or impaired glucose tolerance (IGT) 2-h values in the oral glucose tolerance test (OGTT) in the range from 7.8 mmol/L and 11.0 mmol/L. These persons are referred to as having ‘pre-diabetes’, to indicate their relatively high risk of becoming diabetics in the future. (Expert Committee on the Diagnosis and Classification of Diabetes Mellitus 2003; Genuth et al 2003).

12 Summary of the current biochemical criteria for diagnosis of Diabetes and abnormal blood glucose states according to WHO, 2006:

The diagnostic experience in the former Transkei:

“Comparison of the 1985 WHO and 1997 ADA criteria for the diagnosis of diabetes mellitus in black South Africans. Blanco-Blanco EV, Erasmus RT, AB Okesina, Gqweta Z, Matsha T, Mesa J. 2000. JEMDSA, 5(1):54.

In 1997, the American Diabetes Association (ADA) reviewed the biochemical diagnostic criteria for DM discontinuing the use of the OGTT. In 1999, the World Health Organization (WHO) also introduced the diagnostic fasting plasma glucose at >7.7 mmol/L but the diagnostic use of the OGTT remained unchanged. The latest diagnostic cutoff levels for DM would have an impact on the DM prevalence figures reported with the old criteria (Levitt & Bradshaw 2006). The earlier prevalence needed to be adjusted for the new criteria and new estimates for current and projected burden of DM would follow (Shaw et al 1999). Research from different countries had reported lower diagnostic sensitivity associated with the single use of the Fasting Plasma Glucose for diagnosis of DM as recommended by the ADA. (European Diabetes Epidemiology Group 1999, Ko et al 1998, Gomez- Perez et al 1998).However, this pattern also needed to be validated in the South African settings.

In 2000, the team of researchers from UNITRA (Blanco et al 2000) re-analysed, using the new criteria, the database previously obtained from the OGTT study in factory workers in the former Transkei to compare the diagnostic implications of the changes introduced by both international diabetes organizations. The prevalences for both DM and IGT and for each set of criteria were:

ADA CRITERIA WHO CRITERIA DIABETES MELLITUS DIABETES MELLITUS 2.1% 2.4% IMPAIRED FASTING GLUCOSE IMPAIRED GLUCOSE TOLERANCE 1.9% 2.7% NORMAL FASTING GLUCOSE NORMAL GLUCOSE TOLERANCE 96.0% 94.9%

Implications & Recommendations from the study: The results suggested that the 1997 ADA criteria were less sensitive for diagnosis in black South African diabetics than the OGTT-based WHO criteria as some patients were only identified as diabetics by the OGTT criteria. In addition, the intermediate categories of abnormal glycaemia differed

13 substantially with poor agreement for the IGT category resulting from ADA and WHO new criteria. However, due to the beneficial implications, our findings supported the lowering of the new criteria for Fasting Plasma Glucose. The study also supported the WHO recommendation to continue using the OGTT for the diagnosis of DM in the Xhosa population to avoid misleading estimates of DM burden, and also, more importantly, to prevent the further deterioration of patient as a consequence of a misdiagnosis.

The Risk Factors’ experience in the former Transkei:

Importance of family history in type 2 black South African diabetic patients. Erasmus RT, Blanco-Blanco E, Okesina AB et al ( 2001 b) Postgrad Med J.; 77:323-325.

The family history of diabetes mellitus has been largely discussed in the medical literature as a non-modifiable risk factor for diabetes (Turner, Hattersley & Cook 1992; Simpson 1968). In support of the genetic influence attributed the family history for type 2 diabetes some reports had described concordance rates as high as 60% to 90% for identical twins which is much higher than the one for type 1 diabetes (Newman et al 1987; Barnet et al 1981; Klein et al 1996). In addition, some studies had shown increased frequency of type 2 diabetes in first-degree relatives of diabetic patients (Permut 1990; Hitman & McCarthy 1991). However, little was known of the phenotypic expression and influence of the family history in black African diabetics and therefore the reason for this research. Two groups were created. The patient group made up by type 2 patients attending the diabetic clinic at Umtata General Hospital between 1996 and 1998, and the control group which included healthy subjects recruited from the Umtata district. All participants from both groups were African adults of Xhosa ethnic origin. Demographic and health data were collected. The occurrences of positive family history between the groups were compared. The results suggested that type 2 diabetes has a strong genetic component in black South African diabetics with a predominant tendency to the maternal aggregation. Diabetics with positive family history were found to have an earlier age of onset of diabetes than the rest.

Implications of the study: The strong genetic component for diabetes type 2 in black South Africans provides evidence of the risk associated with family history. It could be, at least theoretically possible, that the risk of diabetes could be lowered by adopting healthier behaviours early in life by the individuals with family history of diabetes type 2. These results provide the platform for potential genotypic studies on the offspring of diabetic patients.

COMPLICATIONS OF DIABETES MELLITUS

Persistent hyperglycaemia in diabetics is unchaining a series of metabolic abnormalities that commonly lead to acute and dangerous complications that constitute medical emergencies.

A study from Tanzania showed that the prognosis for diabetic patients in tropical Africa, even where facilities for care exist, was worse than for patients in developed countries (McLarty et al, 1990). In addition, some reports had stressed the higher morbidity and mortality from diabetes among blacks from Africa as well as from America (Castle & Wicks 1980). These higher rates of complications in blacks are related to disparities in diabetes quality of care, disproportionately poor control of diabetes as well as associated cardiovascular risk factors such as blood pressure and cholesterol (Peek, Cargill & Huang 2007).

14 ACUTE COMPLICATIONS

They include the hyperglycaemic crisis, which often require admission of patients to high-care units and are associated with high mortality rate. Two principal types are recognized, the ketoacidotic and the hyperosmolar (Van Zyl Smit, Burch & Wilcox 2007; Nyenwe et al 2007; Ko et al 2007).

They can present as ketoacidosis with or without hyperosmolarity and hyperosmolar non-ketotic states (Ekpebegh et al 2010; Okoro et al 2007). Combinations of the major types, are also recognized and further classified according to the dominant component into “ketoacidosis with hyperosmolality” and “hyperosmolar state with ketoacidosis” (Levetan, Levitt & Bonnici 1997). The management and outcome of the hyperglycaemic crisis is usually different for these two types (Small, Alzard & Maccuish 1988; Kitabchi et al 2001).

The non-ketotic hyperosmolar state, which is common in type 2 diabetes, is associated with higher morbidity and mortality than the diabetic ketoacidosis which is attributed mainly to high osmolality and older age (MacIsaac et al 2002; Wachtel et al 1991).

A fairly recent review on diabetes classified patients with DKA as the initial manifestation of DM into four categories resulting from the possible combinations (Balasubramanyam et al 2008) which have been used to separate atypical subtypes of diabetes. Combinations of these classifications also identify other variants or subtypes (Katahira 2009).

CHRONIC COMPLICATIONS

The most common body system suffering from the metabolic complications following chronic hyperglycaemia is the vascular system. In general, two main groups of complications are distinguished according to the location of the damage, which are microvascular and macrovascular.

Microvascular complications: In terms of long-term complications of diabetes, the mechanism responsible for complications is the microvascular damage associated with chronic hyperglycaemia leading to progressive dysfunction and failure of different organs, specially the eyes (diabetic retinopathy), kidneys (diabetic nephropathy) and the nerves (diabetic neuropathy). Thus, blindness, chronic renal failure and polyneuropathy are common chronic complications of diabetes. (Levitt et al 1997; Motala et al 2001)

Regarding diabetic complications in the South African context, a 10-year follow up study in black type 1 diabetics in Soweto by Gill, Hiddle & Rolfe in 1995, reported development of retinopathy in 52%, peripheral neuropathy in 42%, autonomic neuropathy in 47% and nephropathy in 28%.

Mbanya and Sobngwi (2003), in a review of diabetic complications in the African continent, described prevalences ranging from 15% to 55% for retinopathy. They also reported the presence of retinopathy in around a quarter of all newly diagnosed type 2 patients. The same study also described diabetes as a risk factor for cataracts and retinopathy in relation to the earlier age of onset of diabetes.

Macrovascular complications: This group results from accelerated atherosclerosis, which is a consequence of the abnormal lipid metabolism and specially the increase in LDL-cholesterol and affects important arteries in the body. It includes mainly: coronary heart disease, cerebrovascular disease (stroke) and peripheral vascular disease (Alberts et al 2005; Kengne, Amoah & Mbanya 2005).

15 The development of combined microvascular and macrovascular disease as in the case of peripheral neuropathy and peripheral vascular disease also contribute to the development of diabetic foot resulting in amputations and locomotion disabilities (Boulton et al 2005; Mbanya & Sobngwi 2003). A review of prevalences of diabetic foot in Africa, reported an 8% for South Africa, being the lowest among the African countries where figures as high as 57% were reported in Nigerian diabetics (Abbas & Archibald (2007).

Another common complication of diabetes is the development of infection. Both, acute and chronic infections are often associated and superimposed on other complications in diabetics (Joshi et al 1999; Shah & Hux 2003).

PREVENTION OF THE DIABETIC COMPLICATIONS:

The presence of diabetic complications increases not only the suffering of the patients, the development of physical disabilities and the mortality rate but also involve increased health costs because they require additional health services and the provision of more specialized level of care. Since the long-term high blood glucose is the starting point for systemic injury that affects most organs in the body, the chronic diabetic complications are preventable, and appropriate glycaemic control is the key to avoid them (Levetan, Levitt & Bonnici 1997; Motala et al 2001).

Taking into consideration all the strategies with evident benefit on the control of the disease and the detection of complications at the earliest phases, when the changes may still be reversible, the international diabetes organizations recommend a set of guidelines to optimize the diabetic care. This set of recommendations is known as “the standards of medical care in diabetes” (American Diabetes Association 2011).

The components of these comprehensive diabetes evaluation guidelines are: A-Medical history: Age, characteristics of onset of diabetes, eating patterns, nutritional status, physical activity, weight changes, diabetes education, treatment history (regimens, control, complications) and psychosocial problems. B-Physical examination: Height, weight, BMI, blood pressure, fundoscopic examination of eyes, comprehensive foot examination and examination of skin and thyroid. C-Laboratory evaluation: Glycosylated Haemoglobin (HbA1c) for the past 3 months or at least within one year, and the fasting lipid profile and liver function tests, test for urine albumin excretion and renal function. D-Referrals for special care eventually needed: Eye care professional for annual dilated eye exam, family planning for women of reproductive age, registered dietician, dentist and mental health professional.

Evaluation of attainment of glycaemic control in diabetics:

The HbA1c is a modification of the normal haemoglobin that occurs in proportion to the levels of blood glucose during the life-span of the red blood cells (3 to 4 months), thus, the higher the glucose values during that time the higher the percentage of glycosylation of haemoglobin. This test, introduced more than 30 years ago, is still the gold standard for evaluation of long-term glycaemic control of the diabetic patients (Gonen et al 1977). A level of HbA1c < 7% is the recommended target for control and prevention of chronic diabetic complications (American Diabetes Association 2011).

16 The presence of persistent albuminuria in the range of 30–299 mg/24 h (known as microalbuminuria) is a well-established marker for development of nephropathy in type 2 diabetes and for the increased risk for cardiovascular diseases. (Garg & Barris 2007; American Diabetes Association 2011).

Commonly suggested strategies in diabetic control such as behavioural changes in lifestyle resulting in a healthier diet, regular physical activity and weight control. Increasing diabetes education and awareness of complications, early diagnosis of the disease, adherence to treatment, access to health care, early detection of complications (clinical and biochemical) are also considered under “the standards of medical care in diabetes”. Hence, strict adherence to these international guidelines warrants the most complete possible diabetic control.

The former Transkei experience on chronic diabetes complications:

Prevalence of diabetic retinopathy in black South African diabetics attending a tertiary clinic in the Eastern Cape. Surka J, Erasmus RT, Blanco-Blanco E, Salazar C, Okesina AB. 2001, JEMDSA, 6 (1): 40.

Diabetic Retinopathy (DR) is a common chronic complication of diabetes and is also one of the most devastating (Javitt & Aielo 1996). DR had been reported the leading cause of new blindness in people aged 25-74 years in developed countries (DCCT 1995). Some well-defined studies had documented prevalences of diabetic retinopathy in (DCCT 1995, Rolfe 1988, Erasmus et al 1989a) but reports in the black population of South Africa were scarce. The records of diabetic patients attending both the Diabetic and Eye Clinic at UGH were analysed to assess glycaemic control, duration of diabetes and severity of the retinal damage.

The overall prevalence of diabetic retinopathy was 21.8%. The stratified prevalences were similar in newly diagnosed diabetics and those with duration of diabetes <10 years(13%) while in patients with diabetes for >10 years it increased significantly (40.7%). The frequency and severity of diabetic retinopathy showed negative association with the deterioration of glycaemic control measured by Glycosylated Haemoglobin.

Implications of the study: The prevalence of diabetic retinopathy in the studied black South African population of the former Transkei was identified and the regular fundoscopic examination was introduced for all diabetic patients receiving care at UGH.

The high prevalence of retinopathy in newly diagnosed diabetics suggested the possibility of high prevalence of undiagnosed diabetes mellitus in the studied population which could explain the presence of chronic complications identified at the time diagnosis was made.

Implications: The confirmation of the prevalence of undiagnosed diabetics requires further community-based studies.

Hypertension, proteinuria and renal insufficiency in black South Africans with non-insulin dependent diabetes. Erasmus RT, Blanco-Blanco E, Okesina AB. 1999(b), Diabetes International. 9(3): 66-69.

This study was motivated by the evidence of the increasing burden of diabetes in South Africa specifically in the urban black African population (Levitt et al 1993 urban African). There was also evidence of frequent association of diabetes with hypertension reported by the National Health and Nutrition Survey (1976-1980) from USA for black Americans (Current Population Survey 1989), and

17 also a similar trend reported in urban and rural black-South Africans (Mollentze et al 1995). Renal insufficiency was a relatively common complication of hypertension in black populations (Mhando et al 1980; Nelson et al 1988)

Data was gathered and analysed for blood pressure, presence of microalbuminuria and/or renal insufficiency as well as obesity in black South Africans attending the diabetic clinic at UGH.

The overall prevalence of hypertension in diabetics was 53%. This pattern was similar to other studies reported from black African populations. No significant differences for age, gender, duration of diabetes, obesity and type of treatment were found. Both proteinuria and azotaemia were independently associated with the development of hypertension.

Implications: There is need to establish early interventions to predict the development of hypertension and renal failure in diabetic patients as the presence of these complications implies an increase in the economic burden of diabetes due to higher morbidity.

The experience on acute metabolic diabetic complications in the former Transkei:

Hyperglycaemic crisis in the Eastern Cape province of South Africa: high mortality and association of hyperosmolar ketoacidosis with a new diagnosis of diabetes. (Ekpebegh CO, Longo-Mbenza B, Akinrinmade A, Blanco-Blanco E, Badri M, Levitt NS 2010, SAMJ, 100 (12): 822-826)

Literature on the clinical, laboratory findings and outcome of the combined presentation as “hyperosmolar diabetic ketoacidosis” from different populations is scarce (Zouvanis et al 1997). The frequency and outcome of these metabolic complications of diabetes, in the population served by the Nelson Mandela Academic Hospital in Umtata, was unknown. This research intended to cover such description by describing the findings of the hyperglycaemic complications in a period of two years. Hyperglycaemic crisis accounted for 43.5% of all diabetic admissions in the period studied. They comprised, in order of frequency, hyperglycaemia (HG) with 44.2%, non-hyperosmolar diabetic ketoacidosis with 36.1%, hyperosmolar hyperglycaemic state (HHS) with 10.8% and hyperosmolar diabetic ketoacidosis (HDKA) with 8.9%.

The study allowed the identification of the Hyperosmolar Diabetic Ketoacidosis (HDKA) as the most common hyperglycaemic presentation associated with the newly diagnosed type-2 diabetes, which was also frequently associated with altered level of consciousness and an alarmingly high mortality rate of 37.5%; in fact, the highest mortality among all diabetic hyperglycaemic crises. This mortality rate was about twice the one reported in other South African study in 1997 (Zouvanis et al).

Implications: The high association of ketoacidosis in addition to the hyperosmolarity reported in this study for type 2 diabetics implies that newly diagnosed type diabetics, at least in this population, are often presenting with a much more complex metabolic model, which requires a somewhat different therapeutic approach. Early identification of the HDKA and awareness of its frequency in the population are the first steps to improve the outcome of these patients.

18 Recommendations: The diabetes subtype regarding insulin reserve and immunity status of these patients needs to be investigated.

The former Transkei experience of acute metabolic complications of diabetes:

Islet immunity and beta cell reserve of indigenous black South Africans with ketoacidosis at initial diagnosis of diabetes. Ekpebegh C; Longo-Mbenza B; Blanco-Blanco E. 2013, Ethn Dis.; 23[2]:196-201

A previous research had shown high prevalence of ketoacidosis combined with hyperosmolality (HDKA) in newly diagnosed black South African patients associated with the highest mortality rate of all hyperglycaemic crises (Ekpebegh et al 2010). Although this pattern had been described before there was little information on the specific phenotype of the patients in this specific population. A recent review classified patients with DKA as the initial manifestation of DM based on islet cell immunity (anti-Glutamic acid decarboxylase antibody) and beta cell reserve into four categories resulting from these combinations (Balasubramanyam et al 2008). Indigenous Xhosa black South Africans with ketoacidosis as the initial manifestation of diabetes were tested for Islet immunity using serum anti-glutamic acid decarboxylase 65 (GAD) antibody beta cell reserve using serum C-peptide after 1 mg of intravenous glucagon.

Results: (A+ b-) antibody positive and beta cell reserve deplete: 22.5% (A+ b+) antibody positive and beta cell reserve replete: 4.2% (A+b-) antibody negative and beta cell reserve deplete: 26.8% (A+b+) antibody negative and beta cell reserve replete: 46.5% The most prevalent pattern was A-b+ suggesting that these patients with ketoacidosis as the initial manifestation of diabetes had islet immunity, beta cell reserve status and clinical profiles of type 2 diabetes.

Implications: The study contributed to establish the subtype of diabetes of those patients presenting with atypical acute metabolic complications (hospital-based). It brings to the attention of doctors the likely risks, complications and specific therapies required for newly diagnosed patients from this population.

Recommendations: The prevalence of these phenotypes in the rest of the diabetic population, specifically for this community, necessitates further studies.

The former Transkei experience on the control and prevention of diabetes complications:

Assessment of glycaemic control in stable type 2 black South African diabetics attending a peri-urban clinic. Erasmus RT, Blanco-Blanco EV, Okesina AB et al. 1999(a). Postgrad Med J, 75(888):603-606.

There was growing evidence suggesting that the prevalence of diabetes mellitus in black South Africans had been steadily rising over the last two decades (Levitt et al 1993). Some studies had described complications observed in diabetics admitted to hospital wards and even post-mortem findings in diabetics with acute metabolic complications but little was known about the glycaemic control of stable black African diabetics attending the out-patient clinics (Bhook 1976; US Department of Health and Human Services 1990). 19 This study was based at Umtata General Hospital; a major referral centre for the former homeland of Transkei. The biochemical determination of glycosylated haemoglobin (HbA1c) was used to assess the long-term glycaemic control. HbA1c values <7% were considered as ‘attaining the target for control’, between 7.1% and 8.9% it was considered “acceptable” whilst >8.9% was ‘poor’.

The results showed poor glycaemic control in the majority of diabetics irrespective of gender, duration of diabetes, adiposity (obesity), educational status, having or not received dietary counselling and, type of pharmacological treatment. Only 20% reached the target for glycaemic control. Possible explanations were related to lack of adherence to advised management and the insufficient dietary counselling probably conditioned by shortage of clinic staff.

Implications: Obesity was present in almost 80% of patients but it did not show any dependence with the glycaemic control. The need for behavioural changes through health educational programmes for both patient and healthcare staff was identified. Intervention strategies were implemented with the collaborative engagement of the departments of Dietetics, Nursing, Internal Medicine and Chemical Pathology based on reported supportive evidence.

Recommendations: The results from this community enquiry completely match our observations from the diabetic patients. Thus, the implications of obesity and its determinants in this community merit further investigation. The implementation of a continuous auditing is recommended to further evaluate attainment of glycaemic control and potential interfering barriers.

Standards of care of diabetic patients at a peri-urban hospital in the Eastern Cape. Erasmus RT & Blanco-Blanco EV. 2000, SA F Pract ; 22(31)17: -20

Following the confirmation of poor glycaemic control in patients attending the diabetic clinic at UGH from a previous research conducted and published (Erasmus et al 2000) the quality of diabetic care provided by the clinic was targeted for evaluation. One of the most effective strategies for attaining control of diabetes and prevent its acute and chronic complications is the use of appropriate and standardized management guidelines in the provision of the continuing medical care (Wayne 1988; Levitt et al 1997; Mash & Levitt 1999).

The standards of the diabetic care provided by UGH were assessed using a structured questionnaire to evaluate their agreement with recommended international guidelines (Alberti & Gries 1998; Santiago 1993). The evaluation referred to two main areas: the processes of care, and, the outcome of the care. Regarding the first criteria, it was found that only 48% of the 23 recommended standards for the process were fully implemented. The original standards not been met were identified. Most of them were related to partial physical examination or laboratory investigations and to deficient patients’ record keeping.

Implications: The identification of the suboptimal standards of medical care for diabetic patients served to understand the problems faced by the clinic and to propose a specific strategy for improvement. This research provided the feedback required for the improvement of the quality of the healthcare provided to the population. The aspects related to the process of care were optimized and a series of diabetes education workshops were organized for both patients and health personnel, specific clinic guidelines were developed and the record keeping was improved.

20 These results were published in the Postgraduate Medical Journal to share the experience and awareness with the medical practitioners in the primary health care (Erasmus et al 2000).

The dietary pattern of black African diabetic patients attending a tertiary care clinic in the Eastern Cape. Mdubeki N, Blanco-Blanco E, Erasmus RT (2001) JEMDSA (6):1, 44.

Recent reports had suggested that a considerable proportion of black diabetics attending the diabetic clinic at UGH were having poor glycaemic control (Erasmus et al, 1999a). Among the factors that contribute to poor control, the patient education with regard to diet and physical exercise plays an important role (Rubin, Peyrot & Saudek, 1989, 1991). Previous studies also reported the effect of urbanisation on the diet of the population. Such changes were suspected to be happening as Umtata is mostly a semi-urban area facing expansion in different directions. The study aimed to investigate the variety of foods regularly eaten by the diabetic patients (food frequency questionnaire) in an attempt to identify potential sources of inappropriate glycaemic control and association with increased adiposity and glycaemic control (Storlien et al 1996).

Randomly selected participants, 62% living in rural areas and 38% from inside the perimeter of the township, were interviewed for food frequency patterns whilst 77% of the total acknowledged having received dietary advice.

The results showed that the food types most regularly consumed (>90%) were starchy foods. Foods eaten in moderate quantities (40-70%) were isigwampa, umbona, umqa and amagwinya. Foods that were not eaten frequently (<30%) were oats, legumes, cereals and pasta. Consumption of vegetables was variable. The most popular meat eaten was chicken, followed by beef. Fish was seldom eaten. About half of the patients were using animal fat for cooking.

Results suggested that the poor diet control, due to high frequency of starchy foods and animal fats, could be at least to certain extent contributing to the overall poor glycaemic control reported on those patients.

There were no differences in the pattern reported between patients who had and who had not received dietary advice.

Implications: Training workshops were organized for clinic staff and patients. The dietetic advice given at the clinic addressed the proper proportions of foods and some recommendations to reduce the intake of animal fats.

Recommendations: Further investigation of the nutritional analysis and food portions in conjunction with the pattern of physical activity was recommended. The effect of dietary advice on diabetics’ behaviour and its relationship with educational background also recalls for further research. Dietary advices must be revised to be in agreement with the local cultural food pattern.

21 Summary of the sequence of events initiated with the suspicion of DM:

The evaluation of glycaemic control and evaluation for chronic complications becomes then a cycle that allow the individual management interventions according to the evolution of the diabetes.

Until this point, I have discussed the implications of diabetes mellitus for the individual patient and the diabetic population. However, I also want to call the attention on the prevalence of diabetes (frequency of the disease out of the total population), the burden of diabetes in terms of total number of people living with the disease as well as the implications of those figures at international, regional and national scale.

THE GLOBAL PREVALENCE & GLOBAL BURDEN OF DIABETES

Diabetes mellitus was considered a disease of minor importance to the world health for long time. However, the past three decades have seen a worldwide explosion in the number of people diagnosed with type 2 diabetes (King & Rewers 1991). This increase has been related to global changes in the human environment, behaviour and the lifestyle associated with increasing rates of obesity. In addition, worldwide achievements in public health with the elimination of many of the communicable diseases during the 20th century resulted in longer life expectancy and higher prevalence of diabetes associated with the ageing population. The current global diabetes epidemic has become one of the main health challenges for the 21st century (Zimmet, Alberti, Shaw 2001; Shaw, Sicree & Zimmet 2010).

In 1993, the WHO Ad Hoc Diabetes Reporting Group (King & Rewers 1993) published a report with standardized global estimates for the prevalence of diabetes mellitus based on data from 75 communities and 32 countries. It is important to note that some epidemiological publications from the early 1990’s did not report separately type 1 from type 2 diabetes, but taking into account that that type 1 is just a fraction of the global figures, the use of data that included both types was not expected to have a major effect on the estimates.

Different countries had already been reporting relatively high prevalence of diabetes mellitus and this study called the attention to the worldwide dimension of the problem not only for diabetes mellitus but also for the pre-diabetic state of Impaired Glucose Tolerance (IGT). The global estimate of people with diabetes from this report for the year 2000 was 154 million. The data used in this study was insufficient to estimate the prevalence for individual countries and to make accurate predictions. However, the impact of this article has led to some global recommendations and target settings as well as to awareness of the need for more community-based data from the different countries.

22 In 1998, King, Aubert & Herman carried out a further version in which they analysed the global database collected by WHO taking into consideration some additional parameters such as sex ratio, urban-rural ratio and age structure of the population. This information was combined with demographic estimates and projections provided by the United Nations to create a new global estimate of prevalence for diabetes mellitus as well as the estimated prevalence for each of the countries of the world and their predicted values for three points in time: 1995, 2000 and 2025. The new estimate for the year 2000 increased by 11%, which means 171 million as compared to the previous 1990 burden number of 154 million. The study resulted in improved estimates for the prevalence of diabetes mellitus in the adult population. However, in addition to the global vision, it introduced estimates of diabetes prevalence for each country in the world in details that included urban-rural ratio, sex ratio, age-structure of population. The latest, more accurate, estimates also included three points in time. Such improved sets of estimates allowed the comparison of the prevalence of diabetes from the different countries across the world and across the major world regions approved by the IDF (Wild et al 2004). The study predicted for the period from 1995 to 2025 a worldwide growth of adult population by 64% with increase in prevalence of diabetes mellitus by 35%, which would result in an increase by 122% in the number of people with diabetes. These impacting figures of the burden of 1990 supported previous forecasts of the global epidemic growth of diabetes for the 21st century. In this report, the extrapolation of available suitable data was used to determine the estimates whenever actual survey data was lacking, for example, all Sub- Saharan Africa was estimated using data from Tanzania. (King, Aubert & Herman 1998).

These studies emphasized the need for survey studies from the different communities and countries in order to obtain accurate data for the current and future prevalences of diabetes. The estimates were set as essential tools to guide the healthcare strategy to manage the burden of diabetes and to identify specific measures expected to neutralize the growing prevalence of diabetes at all levels (Amos, McCarty & Zimmet 1997).

With the subsequent rise of international awareness, some national diabetes surveillance programs developed, providing additional information about diabetes associated disorders and complications and, the World Health Organization recommended the use of the prevalence of diabetes as a basic health indicator (World Health Organization 1997).

Summary of global statistics for diabetes in 2012

• More than 371 million people have diabetes • The number of people with diabetes is increasing in every country • 80% of people with diabetes live in low- and middle-income countries • The greatest number of people with diabetes are between 40 to 59 years of age • Half of people with diabetes are undiagnosed • 4.8 million people died due to diabetes • More than 471 billion USD was spent on healthcare for diabetes.

23 Figure 1. Prevalence of diabetes (%) for world adult population (20-79 years), 2011

Source: IDF Diabetes Atlas, 2011 http://www.idf.org/diabetesatlas

Estimated increase in prevalence for 2030 based on the 2011 estimates (20-79 years)

Source: IDF Diabetes Atlas, 2011 http://www.idf.org/diabetesatlas

24 Figure 2. Percentage of total cases of diabetes (20-79 years) by IDF region, 2011 & 2030:

AFR: Africa EUR: Europe WP: Western Pacific MENA: Middle East and North Africa SEA: South-East Asia NAC: North America and Caribbean SACA: South and Central America

Source: IDF Diabetes Atlas, 2011 http://www.idf.org/diabetesatlas

According to the predictions based on estimates and population growth, the increase in the burden of diabetes by 2030 is expected to have a specific regional pattern as shown in the above graph (Shaw, Sicree & Zimmet 2010; International Diabetes Federation 2011). As shown in the graph, the diabetes prevalence estimates for 2011 and 2030 will not change much within each major world region. However, in terms of the total number of people living with diabetes, most of the increase will emerge from specific areas such as South-East Asia and Africa, because of their higher expected population growth rates. The same pattern applies when comparing the prospected diabetes prevalence figures of developed versus developing countries. The individual prevalences translate into burden of diabetes (total number of people living with diabetes) as a function of the population growth (Shaw, Sicree & Zimmet 2010; King, Aubert & Herman 1998; Levitt & Bradshaw 2006).

According to the WHO projections, diabetes will be the seventh leading cause of death by 2030. Healthy diet, regular physical activity, maintaining a normal body weight and avoiding tobacco use can prevent or delay the onset of type 2 diabetes (International Diabetes Federation 2011).

In 2004, Wild et al reported new estimates for the prevalence of diabetes for the year 2000 and their projections for 2030 published a follow up investigation on the world and country-based estimates of 1990. The resulting new estimate for South Africa in the year 2000 for prevalence of diabetes was based on the data published by Levitt et all in 1993 from urban Africans in Cape Town. The updated estimate published in 2010 by Shaw, Sicree & Zimmet expanded the data which included three additional studies from South Africa published by Omar et al (1993), Erasmus et al (2001a) and Motala et al (2008).

25 THE AFRICAN BURDEN OF DIABETES MELLITUS

The estimated global total of persons living with diabetes mellitus in 2007 was 124 million whilst for 2010 it was 221 million. In Africa the total estimated was 7.8 million with 4.5 million in North Africa, 1.08 million in Western Africa, 1.05 million in Eastern Africa, 0.26 million in Central Africa and 0.82 million in Southern Africa (International Diabetes Federation 2011).

The main features of the burden of diabetes as estimated for 2011 and 2030 in AFRICA are summarized as follows:

Source: IDF Diabetes Atlas, 2011 http://www.idf.org/diabetesatlas

26 The variation in the estimates for diabetes mellitus prevalence in Africa shows some geographic concentration in specific areas where Southern Africa exhibits the highest prevalence.

Figure 3. Prevalence (%) estimates of diabetes (20-79 years), 2011, Africa Region:

Source: IDF Diabetes Atlas, 2011 http://www.idf.org/diabetesatlas

The prevalences of diabetes for Sub-Saharan Africa also show extensive regional variations which are independent of the diagnostic criteria used for diabetes (Mbanya et al 2010).

Another report by Levitt in 2000 using standardised diagnostic reported age-standardized prevalences of diabetes lower than 2% from two communities in Cameroon and four communities in Tanzania whilst in five investigated communities in South Africa the prevalences ranged from 4% to 8%.

THE SOUTH AFRICAN BURDEN OF DIABETES MELLITUS

The initial report of the burden of diabetes as published in 1998 by King, Aubert & Herman, faced a lack of local statistical research data from South African. Thus, the 1990 estimate for prevalence of diabetes in South Africa used an extrapolation of available data from Tanzania reported by McLarty et al in 1989. The use of extrapolated data generated diabetes prevalence estimates of 1.4% for 1995 and 2000 and 1.6% for the year 2025.

In South Africa, after 1994, the research publications on the epidemiology of diabetes were still scarce. The first demographic report emerged from The South African Demographic Health Survey (DHS) conducted in 1998. This survey resulted in a large amount of internal data regarding health issues from more than 13 000 adult male and female participants starting from the age of 15 years. The resulting prevalences of diabetes by province showed significant differences as compared to previously published estimates as was the case for the prevalences per population group (Steyn, Fourie & Temple 2006, Chapter 10, p110). The DHS (1998) was a breakthrough in terms of making available information generated within the country; new estimates, which were closer to the South African reality, were calculated and even stratified per province, age groups, population groups,

27 urban-rural ratio and sex ratio. However, the data still had limitations arising from the self-reported nature of the data collected; the report missed the undiagnosed diabetics. In summary the diabetes prevalence resulting from the DHS 1998 were: ALL URBAN NON-RURAL Males 2.4% 2.9% 1.7% Females 3.7% 4.4% 2.7%

In 2003, a second round of the South African DHS led to a new report but the self-reported prevalences for diabetes did not change significantly between them both (Levitt NS. 2008).

Table 2. Example of the original DHS 1998 data report. The specific section referred to “chronic disease prevalence among men”.

BACKGROUND HYPER- ISCHAEMIC STROKE HYPERLI- DIABETES EMPHYSEMA ASTHMA CANCER NUMBER CHARACTERISTIC TENSION HEART PIDAEMIA CHRONIC S DISEASE BRONCHITIS AGE 15-24 0.2 0.3 0 0.2 0.1 2.3 2.9 0.0 1.812 25-34 2.7 1.9 0.7 1.2 0.8 2.8 1.9 0.2 1.120 35-44 7.5 2.9 0.5 1.8 2.5 3.0 4.0 0.0 1.003 45-54 18.0 4.6 2.0 4.3 5.4 8.7 7.7 0.6 700 55-64 16.9 6.6 2.0 3.8 7.9 6.7 5.4 0.1 514 65+ 25.0 7.8 2.3 3.7 4.8 8.6 7.3 1.6 502 Residence URBAN 9.4 3.1 0.7 2.2 2.9 4.9 4.1 0.3 3.569 NON-URBAN 5.5 2.4 1.2 1.2 1.7 3.2 3.2 0.2 2.102 PROVINCE WESTERN CAPE 9.2 2.8 0.9 1.7 3.2 9.4 4.6 0.4 721 EASTERN CAPE 9.0 3.5 0.9 1.3 2.7 5.2 4.7 0.3 758 NORTHERN CAPE 13.2 4.1 1.3 1.8 2.1 5.6 3.2 0.2 135 FREE STATE 7.2 2.6 0.4 1.4 1.3 0.7 1.3 0.4 444 KWAZULU-NATAL 7.5 3.2 1.6 1.7 3.1 3.4 4.9 0.2 1.064 NORTH WEST 4.8 2.4 0.3 1.1 0.9 1.4 2.4 0.0 551 GAUTENG 10.7 3.1 0.7 4.0 3.3 5.7 4.5 0.5 1.099 MPUMALANGA 4.9 1.8 1.1 0.9 2.0 2.9 2.9 0.2 378 NORTHERN 4.4 2.0 0.5 0.2 0.9 1.1 1.3 0.2 521

Source: Department of Health, 1998. South Africa Demographic and Health Survey, 1998: Full report. Pretoria: South Africa (table 10.3).

The table shows a portion of the original table 10.3 of the DHS 1998 report, which illustrates the considerable degree of details in the information collected and an example of the variations of prevalence for diabetes across the provinces. The high statistical variability observed in the reported prevalences of diabetes from different geographic areas and socioeconomic settings even within the same populations groups supports the notion that each of the various risk factors associated with diabetes do not have the same intensity and influence across the country. It also emphasizes the need for developing community-based research that provides better perception of the complexity ruling the different settings (Zimmet 1999). The evidence of those particularities supports the inferred principle that the identification of the pattern inherent to each community is the key to identify the relevant strategies to counteract the rampant growth of diabetes (King, Aubert & Herman, 1998; Shaw, Sicree & Zimmet 2010; Hall et al 2011).

28 COMMUNITY-BASED STUDIES IN SOUTH AFRICA:

In the late 90’, some cross-sectional prevalence studies from South Africa were published. The first one by Charlton, Levitt & Lombard (1997) had some limitations, as it was restricted to the elderly sub-population of coloured South Africans. Another one by Levitt et al followed this report in 1999, which reported an age-standardised prevalence of 10.8% in a coloured community of the Western Cape. (Steyn, Fourie & Temple 2006, Chapter 10, p.111).

In 2001 a study by Erasmus et al (2001a) done in Black Africans in Umtata was published reporting an age-adjusted prevalence of 4.5%. In both studies the age-adjusted prevalences of diabetes were found to be higher than the ones previously reported by the DHS for their respective provinces and population groups. These studies provided the first South African reports of cross-sectional community research data, and the information was used in the following DM burden estimates (Shaw, Sicree & Zimmet 2010, Hall et al 2011). A few other papers have been published on other population groups in South Africa. In the year 2000 there were at least 6 prevalence reports on diabetes published from different population groups in South Africa which were used in the following works on re-estimates for the world, the IDF regions and the different countries.

Table 3. Available research reports on prevalence of diabetes from South Africa by 2000 as per records of the IDF Diabetes Atlas:

Population Region (number of par- Preva- Age Reference ticipants) lence range (%) African Cape Town, urban (729) 8.0 30 + Diabet Care 1993;16:601 African QwaQwa, rural (853) 4.8 25 + S Afr Med J 1995;85:90 Mangaung, urban (758) 6.0 African Durban, urban (479) 5.3 15 + S Afr Med J 1993;83:641 Mixed Cape Town, urban (200) 28.7 65 + S Afr Med J 1997;87 (suppl 3):364 Mixed Cape Town, peri-urban (974) 10.8 15 - 86 Diabet Med 1999;16:946

European Durban, urban (396) 3.0 15 - 69 S Afr Med J 1994;84:257 Indian Durban, urban (2479) 13.0 15 + Diabet Care 1994;17:70

Source: IDF Diabetes Atlas, 2011 http://www.idf.org/diabetesatlas

The experience in the former Transkei:

Prevalence of diabetes mellitus and impaired glucose tolerance in factory workers from Transkei, South Africa. Erasmus RT; Blanco EB; Okesina AB et al 2001(a). SAMJ, 91(2 I):157- 160.

The 1990 and 1995 reports on the global burden of DM and its projected increase with epidemic dimension had been reported (King & Rewers 1991, 1993). The published figures put in evidence the high variability of the prevalence of type 2 diabetes mellitus for the different communities and population groups even in the same geographic areas Ahren & Corrigan 1984, McLarty et al 1989, Erasmus et al 1989b).

29 Other reports had demonstrated that the increase in prevalence of diabetes in developing countries, which in some instances exceeded that of the developed ones. Data regarding the prevalence of diabetes for the South African population was lacking. The South African Demographic Health Survey of 1998 (DHS report 1998) provided extensive information from all geographic latitudes, population groups and ages but the data had the limitations inherent to a self-reported process, and, in addition, previous studies had reported a relatively high number of undiagnosed diabetics in the African region. Some community-based research reports were emerging with information from specific South African populations, (Levitt et al 1993; Omar et al, 1993) but very scarce community-explored data was available on the prevalence of DM in the Xhosa population of the former Transkei where the University of Transkei is located. There was a need for a response from the local community to investigate the issue and to contribute to the identification of a more realistic estimate of the prevalence of DM in the country, the provinces and their individual communities and population groups.

The strategy followed was the recruitment of workers from two of the largest factories in Umtata. An oral glucose tolerance test (OGTT) was performed on each of the 374 black African Xhosa respondents with ages ranging from 20 to 69 years. Basic personal demographic and anthropometric data was also collected. Statistical transformation of frequencies to the standard world population was used to obtain age-adjusted prevalences.

The critical values obtained were: Diabetes mellitus: Crude prevalence: 2.5% Age-standardized: 4.5 % (CI 1.54; 7.42) Impaired Glucose Tolerance: Crude prevalence: 2.7% Age-standardized: 5.1 % (CI 2.45; 5.51)

A remarkable finding of this research was that 89% of the workers found to be diabetics had not been diagnosed before which suggests that the prevalence of undiagnosed diabetes in the Xhosa community around Umtata could be considerably high. However, the confirmation of these figures merits further exploration. In contrast with most reports from similar populations, obesity was only present in 22% of workers with no gender differences. It was also a contrasting finding the lack of association between obesity and diabetes mellitus although there was some relationship between the IGT and the presence of overweight. Some association was expected, taking into consideration that, the frequency of obesity, reported for stable patients attending the diabetic clinic at Umtata General Hospital, was 79.4%. Further epidemiological studies on randomized larger samples were recommended to explore the prevalence of type 1 DM and the impact of obesity on the prevalence of DM in the community studied.

Implications: The most relevant outcome was the establishment, for the first time, of the crude and the age- adjusted prevalences of DM and IGT for the Xhosa population of Umtata obtained by direct diagnostic testing of a sample from the community. The results were published and shared, nationally and internationally. These figures have served as reference by other researchers to compare tothe other South African communities. They have also been included in the data used to generate new estimates of the burden of DM in South Africa and in closely related countries where this kind of information has not been available (Shaw, Sicree & Zimmet 2010, Hall et al 2011).

30 DIABETES AND THE BURDEN OF COMMUNICABLE DISEASES IN AFRICA

One overriding influence to consider when estimating the prevalence of non-communicable diseases in the African region is the potential opposing effect exerted by co-existing epidemics of communicable diseases such as HIV/AIDS and tuberculosis. Changes in the population structure and the population growth rate could prevent the doubling effect expected in future estimates of prevalence for diabetes (Levitt & Bradshaw 2006). Hence, we must consider the potential impact of the HIV/AIDS epidemic on the population growth when estimating the prevalence of diabetes. The HIV burden and its effects on the estimates for prevalence of diabetes in South Africa:

In 1999, Panz and Joffe reported an estimated increase in the burden of diabetes in South Africa from 1.6 million in 1995 to 3.5 million in 2010. The 2010 predicted prevalence of diabetes, recalculated in view of the effect of HIV/AIDS was only 100 000 cases less. In 2005, a study by Levitt & Bradshaw using the 2001 census data published improved estimates of the burden of HIV/AIDS and prevalence of diabetes. The result was an estimated reduction of the population growth from 1.8% per annum in the absence of HIV/AIDS to 1.1% per annum because of the HIV/AIDS epidemic. Levitt also revised the estimates in 2008 with new data reported and using more complex prediction models, which still supported the South African population growth rate to increase at 1.5%. Thus, the prevalence of diabetes would also increase, resulting only in little change compared to the previous estimates for the burden of diabetes. Similar extrapolations support the projected estimates for the rest of Africa. We must also consider that the expansion of the ARV program is lowering the impact of the HIV/ AIDS epidemic on the population growth and, in addition, a growing number of studies are reporting increased association of diabetes/metabolic syndrome with the use of ARV therapy.

Tuberculosis and the prevalence of diabetes in South Africa:

The increased susceptibility to infections secondary to the metabolic effects of diabetes mellitus is a well-documented fact supported by the high incidence of sepsis as acute complications in diabetic patients (Joshi et al 1999, Shah & Hux 2003).

Recent studies demonstrated increased chance of developing tuberculosis by at least 2.5 times in the presence of diabetes (Ottmani et al in 2010). In addition, a person with diabetes and tuberculosis is more likely to fail tuberculosis treatment and more likely to die from tuberculosis than a person without diabetes (Goldhaber-Fiebert et al 2011, Baker et al 2011).

Diabetic control is beneficial in reducing the risks of tuberculosis although the association of these diseases also depends on other social determinants (Leung et al 2008). The increasing burden of diabetes is expected to produce a corresponding increase in the burden of tuberculosis. Hence, it poses a threat to the attainment of the Millennium Development Goals on tuberculosis (Goldhaber- Fiebert et al 2011).

31 Figure 4. Percentage of tuberculosis cases attributable to diabetes (20-79 years), 2011.

Source: IDF Diabetes Atlas, 2011 http://www.idf.org/diabetesatlas

THE SOUTH AFRICAN FIGURES FOR DIABETES

The estimated prevalence of diabetes in South Africa in 2012 was 7.0%. Although it is not amongst the highest in the world, the translation in terms of total number of diabetics results in a enormous amount when predicted as to be double in a decade.

Although the prevalence of diabetes in South Africa is not amongst the highest in the African region, in terms of total people living with diabetes, South Africa, at 1.9 million, is only second to Nigeria with 3 million; this effect is largely due to the population size (International Diabetes Federation 2011). Similar translation is required when analysing the South African reports on prevalences of risk factors and diabetes death rates shown in figure 5.

32 Figure 5. Summary statistics for non- communicable diseases in SOUTH AFRICA (2011) as compared to the current leading causes of death.

Source: World Health Organization 2011- NCD Country Profiles.

Summary of the South African estimates for diabetes mellitus (DM) and Impaired glucose tolerance (IGT), (20-79 years).

2011 2030

TOTAL POPULATION 30 111 820 35 422 200

PREVALENCE OF DM 6.5% 7.2%

TOTAL PEOPLE LIVING WITH DM 1 946 600 2 548 100

PREVALENCE OF IGT 7.0% 8.0%

TOTAL PEOPLE LIVING WITH IGT 2 113 100 2 846 500

DEATHS ATTRIBUTED TO DM 3%

TOTAL DEATHS ATTRIBUTED TO DM 63 061

TOTAL UNDIAGNOSED DIABETICS 1 557 300

DM-RELATED MEAN EXPENDITURE 695 U.S.D PER PERSON WITH DIABETES

Source: Source: IDF Diabetes Atlas, 2011, 5th Ed http://www.idf.org/diabetesatlas

33 CONSEQUENCES OF THE BURDEN OF DIABETES

SOCIOECONOMIC CONSEQUENCES

The human and social issues Diabetes is a global epidemic that results in devastating consequences to the society, the family and the diabetic individuals. In terms of society, the diabetes epidemic implies millions of people living with this chronic disease, with the associated costs of therapy, which become higher in the presence of associated acute and chronic complications (Anderson et al 1997). The commonly faced economic disability, death and related financial distress secondary to diabetes, can cause quite a social drama at the level of the family. In terms of the person, the quality of life of diabetic patients in general is just not as satisfactory as for individuals without chronic diseases (Trief et al 1998). In addition, increasing levels of deterioration of their quality of life arrive with their adaptation to dietary modifications, treatment choices (insulin injection versus oral hypoglycaemic drugs), glycaemic control and also with the presence of associated complications (Rubin and Peyrot 1999). Rose et al (1998) described that the whole self-perception of quality of life by these patients changes as ‘a function dependent on psychosocial factors such as health and cultural beliefs, social support, coping strategies and personality traits’.

The Economic issues Dall et al (2010) highlight two important aspects in the economic burden of diabetes. These can be divided into direct and indirect cost. The direct cost is the cost attributable to health care services and, the indirect cost is due to productivity loss associated with diabetes. The direct health care costs for diabetes include the costs for ambulatory management, for treating the diabetic medical emergencies and for the in-ward hospital admissions. On the other hand, the indirect costs are the losses affecting the economy by reducing the productivity arise from increased rates of absenteeism, reduced productivity whilst at work, disability that prevents work and premature death. The increased financial burden of diabetes affects the national economies by “competing” for funds with the other national priorities (Dall et al 2010).

The estimate of the economic burden for the 17.5 million people living with diabetes in the U.S.A in 2007 is $174.4 billion, with an estimate of $159.5 corresponding to type 2 diabetes. (Dall et al 2010). For 2012, the American Diabetes Association (2013b) reported a 41% increase over the initial estimate, making a total estimate of $245 billion.

The instrumental models used to estimate the epidemiological and economic burden of diabetes require accurate records to derive reliable current and prospected figures that actually correspond to the national particularities and guide their strategic plans.

34 Figure 5. Total healthcare expenditures due to diabetes (20-79 years) (USD), R=2*, 2011:

Source: IDF Diabetes Atlas, 2011 http://www.idf.org/diabetesatlas

The figure reflects the potential influences of the socio-economic development, type of economy and national internal product as a source of disparities in the healthcare expenditures for diabetes for the different regions.

According to the International Diabetes Federation (International Diabetes Federation 2011): • The North America and Caribbean Region spent an estimated USD 223 billion or 48% of the global healthcare expenditures for diabetes in 2011. • The Europe Region spent about half that amount at USD 130 billion. These two regions combined had the highest expenditures due to diabetes in 2011. • In comparison, the Western Pacific Region spent only USD 72 billion on diabetes healthcare despite having the largest number of people with diabetes. • The South and Central America and Middle East and North Africa Regions each spent less than 5% of the global total on healthcare expenditures due to diabetes, while, • The Southeast Asia and Africa Regions spent less than 1% in 2011.

The basic data in figure 5 is based on extrapolations and estimates calculated from the total healthcare expenditures. The actual individual cost of care per diabetic patient per year in South Africa is not available.

IMPLICATIONS OF THE BURDEN OF DIABETES FOR HEALTH PLANNING

There are two important perspectives of the socioeconomic impact of the burden of diabetes. One is regarding the implications arising from the projected growing burden of diabetes and the other relates to implications for the people already living with diabetes.

35 DIABETES PREVENTION AS STRATEGY

The value of community-based research and community-based preventive interventions: The socioeconomic impact implied by the projected burden of diabetes calls for community-based health interventions addressed to prevent the further increase of the total number of people living with diabetes. Diabetes prevention as a strategy encompasses, in the first place, the identification of the dominant pattern of contributing risk factors for diabetes in each community. Although prevention strategies also involve added healthcare costs, experiences from some intervention trials have demonstrated that investing in preventative programs is likely to reduce the transit from pre- diabetic status into diabetes, which in turn decreases the cost of managing diabetes mellitus and its complications (WHO 1994). However, there are no off-the-shelf interventions to be effectively extrapolated from other studies as the impact cannot be the same in different settings. Thus, the planning process for community interventions must rely on the availability of data representative of the risk expressed in each community. For example, in the case of South Africa, we have seen the statistical evidence of the different prevalences across population groups, geographic areas, sociocultural background, etc. Thus, a unique prevention plan is not likely to improve cost-effectively the situation in the whole country (Unwin et al 2001).

For the selection of possible strategies, before embarking on the planning, some questions that need answers are: • Are the projections for the burden of diabetes in this community accurate? • What is the actual number of people living with diabetes, in this community? • Do they even know they have diabetes? • Which risk factors are paramount in our community? Are they modifiable? • Would the expected impact of such intervention justify the cost of its implementation?

Such questions are not easy to answer. The answers need a body of evidence extracted from community-based research. Academic institutions play a key role in obtaining these epidemiological information from their communities (Unwin et al 2001; Mbanya 2010).

The relevant population data generated from community studies establish the grounds on which the higher education institutions and the community recommend and provide supportive expertise to health policy makers and health administrators to oversee the strategic and cost-effective design of the preventive interventions (Zimmet 1999).

The estimation of the cost-effectiveness of diabetes prevention strategies regarding costs, quality of life, and health outcomes is necessary to deliver a cost analysis that goes beyond total costs but rather defines costs translated into improved quality of life. One of the recommended units is the cost per quality-adjusted life-year gained over a lifetime (Herman et al 2005). Additionally, the higher cost-effectiveness of the prevention programs can be attained by using an integrated approach, which is not only dealing with the prevention of diabetes but also, at the same time, targets other coexisting risk factors such as those for cardiovascular diseases. The integrated approach allows the sharing of common resources and avoids the duplication of programs (Simmons, Griffin & Wareham 2007; Alberti, Zimmet & Shaw 2007).

The collaborative participations by the three parties: academy, community and health authority then continues the cycle during the implementation and the evaluation of the interventions.

Numerous interventions for the prevention and control of diabetes have proven to be beneficial in different settings (Jamison et al, 2006, Chap. 5, p.594). 36 Examples of typical diabetes interventions, at different stages, and their reported benefits:

COST EFFECTIVENESS RA- TIO (US$/ quality-adjusted BENEFIT STRATEGY life year)

Preventing diabetes

Lifestyle interventions for pre- Reduction of 35% - 58% in inci- 1,100 (Diabetes Prevention Pro- venting type 2 diabetes dence among people at high risk gram Research Group forthcom- ing)

Metformin for preventing type 2 Reduction of 25% - 31% in inci- 31,200 (Diabetes Prevention diabetes dence among people at high risk Program Research Group forth- coming)

Screening for diabetes

Screening for type 2 diabetes in Reduction of 25 % in microvas- 73,500 (CDC Diabetes Cost-Ef- general population cular disease fectiveness Study Group 1998)

Treating diabetes and its complications

Annual screening for microalbu- Reduction of 50% in nephropa- 47,400 (Klonoff and Schwartz minuria thy using ACE inhibitors for iden- 2000) tified cases

Annual eye examinations Reduction of 60% to 70% in se- 6,000 (Klonoff and Schwartz rious vision loss 2000; Vijan, Hofer, and Hayward 2000) (Jamison et al, 2006, Chap. 5, p.594)

CONTROL OF THE CURRENT BURDEN OF DIABETES

Targeting specific standards of care for diabetes

Improving standards of care for diabetes to improve glycaemic control and prevent the development of complications can reduce the socioeconomic impact of the current burden of diabetes. It can do this by decreasing associated morbidity, diabetic emergencies, related disabilities and death as well as improving the quality of life of the people living with diabetes.

This aspect has a stronger public healthcare perspective as it is more related to management interventions addressed to patients who already live with the disease. However, as it happens with the prevention, strategies for controlling the current burden of diabetes, also need research inputs. to show the directions to be strengthened according to the prevalences of complications in the diabetic population and challenges in their management. Research is also necessary to evaluate the effectiveness of the implemented management interventions.

Although the supportive reports on this aspect are more likely to emerge from healthcare centres rather than from community studies, the collaborative and integrated strategy recommended in the

37 prevention is also a powerful cost-effective method for the control of the disease (Unwin et al 2001; Mbanya 2010; Simmons, Griffin & Wareham 2007; Alberti, Zimmet & Shaw 2007).

It is necessary to emphasize the need to publish the results and statistics of the conducted research in scientifically recognized sources to be shared with the international scientific community and with the international diabetes organizations, to provide updated data to be used when calculating new estimates and their impact of the various local, national and regional interventions on the burden of diabetes.

Some areas requiring further research attention in South Africa: • The current epidemiological burden of diabetes to see how much it has actually increased (validation of estimates) • The pattern of prevalence of diabetes for rural and urban populations • The current prevalence of type 1 diabetes • The current financial burden of diabetes • The current prevalence of diabetic complications

In addition to the above areas, the following arise from the experiences in the former Transkei: • The prevalence of undiagnosed diabetes • The effect of obesity as a risk factor for diabetes in the community • The complete model of nutritional assessment and physical activity using validated protocols for both the general and the diabetic population. • The progressive evaluation of the quality of diabetic care provided • The genetic linkages related to the family history

38 CONCLUSIONS

The emerging epidemic of type 2 diabetes is a global problem requiring global attention and urgent action.

The predicted progression of the type 2 diabetes epidemic in South Africa constitutes a threat to public health and the economy that needs the development of timely cost-effective interventions, however, further urgent community research is vital to validate the current estimates.

The control of the burden of diabetes in South Africa requires collaborative and coordinated action from different sectors at all levels; the three more prominent probably are the Department of Health, the Academic Institutions and Communities. Some strategic tasks to be addressed are: • The development and implementation of cost-effective health strategies to provide integrated & coordinated care in response to the needs of the community and adapted for the administrative structure in place. • The development of human resources capacity to provide appropriate multidisciplinary support to patients and healthcare programs at all levels. • The intensification of community health education to foster healthier lifestyles, improve the patient’s participation in self-control and self-monitoring of diabetes, community ownership of health programs, and alleviation of the shortage of staff. • Academic institutions to provide the research expertise needed from all different perspectives of the problem (healthcare, epidemiology, economic, cultural, educational, nutritional, psychological, etc.) by using their research capacity and gaining access to research resources from local government and from external funding agencies. Furthermore, academic institutions must address any needed curricular changes to ensure that the outgoing professionals are relevant to the needs of the communities.

39 REFERENCES

Abbas Z, Archibald L. 2007. The diabetic foot in sub-Saharan Africa: a new management paradigm. Diab Foot J 10: 128-36.

Ahren B, Corrigan CB. 1984. Prevalence of diabetes mellitus in North Western Tanzania. Diabetologia 26: 333- 36.

Alberti KG, Zimmet P, Shaw J. 2007. International Diabetes Federation: a consensus on Type 2 diabetes prevention. Diabet Med. 24(5):451-63.

Alberti KG; Gries FA. 1988. Management of non-insulin-dependent diabetes mellitus in Europe: a consensus view. Diabetic Med 5: 275-281.

Alberts M, Urdal P, Steyn K, Stensvold I, Tverdal A, Nel JH, Steyn NP. 2005. Prevalence of cardiovascular diseases and associated risk factors in a rural black population of South Africa. Eur J Cardiovasc Prev Rehabil 12:347-354.

American Diabetes Association and National Institute of Diabetes, Digestive and Kidney Diseases. 2002. Position statement: the prevention or delay of type 2 diabetes. Diabetes Care 25, 742–749.

American Diabetes Association. 2009 International Expert Committee report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care. 32: 1327-1334.

American Diabetes Association. 2011. Standards of medical care in diabetes–2011. Position statement. Diabetes Care 34(1):S11-S61.

American Diabetes Association. 2012. Standards of medical care in diabetes. III. Detection and diagnosis of gestational diabetes mellitus (GDM). Diabetes Care 35 (Suppl 1):S15-6.

American Diabetes Association. 2013a. Diagnosis and Classification of Diabetes Mellitus. Position statement. Diabetes Care. 36 (S1) S67-74.

American Diabetes Association. 2013b. Economic Costs of Diabetes in the U.S. in 2012 Diabetes Care. 36 (4) 1033-1046.

Amoah AG, Owusu SK, Adjei S. 2002. Diabetes in Ghana: a community based prevalence study in Greater Accra. Diabetes Res Clin Pract 56: 197–205.

Amos A, D. McCarty, P. Zimmet. 1997. The rising global burden of diabetes and its complications: estimates and projections to the year 2010, Diabet Med. 14, Suppl. 5, S1-S85.

Anderson RM, Fitzgerald JT, Wisdom K, Davis WK, Hiss RG. 1997. A comparison of global versus disease-specific quality-of-life measures in patients with NIDDM. Diabetes Care 20: 299-305. 40 Assah FK. 2009. Physical activity, cardiorespiratory fitness and metabolic health in Cameroon [PhD Thesis]. Cambridge: University of Cambridge.

Baker MA, Harries AD, Jeon CY, et al. 2011. The impact of diabetes on tuberculosis treatment outcomes: A systematic review. BMC Med 9: 81.

Balasubramanyam A, Nalini R, Hampe CS, Maldonado M. 2008. Syndromes of ketosis-prone diabetes mellitus. Endocr Rev 29:292.

Barnett AH, Eff C, Leslie RDG, Pyke DA. 1981. Diabetes in identical twins. A study of 200 pairs. Diabetologia 20:87–93.

Bhook KD. 1976. A necropsy study of diabetes mellitus in Natal blacks. S Afr Med J; 50:1361-6.

Blanco-Blanco EV, Erasmus RT, AB Okesina, Gqweta Z, Matsha T, Mesa J. 2000. Comparison of the 1985 WHO and 1997 ADA criteria for the diagnosis of diabetes mellitus in black South Africans. JEMDSA- 2000, JEMDSA, 5(1):54.

Boulton AJ, Vileikyte L, Ragnarson-Tennvall G, Apelqvist J. 2005. The global burden of diabetic foot disease. Lancet 366:1719-1724.

Bourne LT, Lambert EV, Steyn K. 2002. Where does the black population of South Africa stand on the nutrition transition? Public Health Nutr 5: 157–62.

Castle WM, Wicks ACB. 1980. A follow up of 93 newly diagnosed African diabetics for 6 years. Diabetologia 18:121–3.

Charlton KE, Levitt NS, Lombard CJ. 1997. The prevalence of diabetes mellitus and associated risk factors in elderly coloured South Africans. S Afr Med J 87: 364-367

Christensen DL. 2008. Glucose intolerance in relation to body composition, physical activity and other predictors among the Luo, Kamba and Maasai of Kenya [PhD Thesis]. Copenhagen: University of Copenhagen.

Current Population Survey (CPS). 1989. National Centre for Health Statistics, National Health and Nutrition Survey, 1976 - 1980. Cardiovascular Risk factors Supplement.

Dall TM, Zhang Y, Chen YJ, Quick WW, Yang WG, Fogli J. 2010. The economic burden of diabetes. Health Aff (Millwood) 29: 297–303.

Dehanty LM, Halford BN. 1993. The role of diet behaviours in achieving improved glycaemic control in intensively treated patients in the DCCT Trial. Diabetes Care, 16, 1453- 58.

41 Department of Health, 1998. South Africa Demographic and Health Survey, 1998: Full report. Pretoria: South Africa.

Ekoe J-M, Rewers M, Williams R, Zimmet P, Eds. 2008. The epidemiology of diabetes mellitus (2nd ed). Chichester: Wiley: 133–46

Ekpebegh CO, Longo-Mbenza B, Akinrinmade A, Blanco-Blanco E, Badri M, Levitt NS. 2010. Hyperglycaemic crisis in the Eastern Cape province of South Africa: High mortality and association of hyperosmolar ketoacidosis with a new diagnosis of diabetes. SAMJ. 100 (12): 822-826.

Ekpebegh C; Longo-Mbenza B; Blanco-Blanco E. 2013. Islet immunity and beta cell reserve of indigenous black South Africans with ketoacidosis at initial diagnosis of diabetes. Ethn Dis. 23[2]:196- 201.

Elbagir MN, Eltom MA, Elmahadi EMA, Kadam IMS, Berne C. 1996. A population-based study of the prevalence of diabetes and impaired glucose tolerance in adults in northern Sudan. Diabetes Care 19: 1126–28.

Elbagir MN, Eltom MA, Elmahadi EMA, Kadam IMS, Berne C. 1998. A high prevalence of diabetes mellitus and impaired glucose tolerance in the Danagla community in northern Sudan. Diabet Med 15: 164–69.

Erasmus RT, Alanamu RA, Bojuwoye B, Oluboyo P, Arije A. 1989a. Diabetic retinopathy in Nigerians: relation to duration of diabetes, type of treatment, and degree of control. East Afr Med J. 66(4):248– 254.

Erasmus RT, Fakeye T, Olukoga O, Okesina AB, Ebomoyi E, Adeleye M, Arije A. 1989b. Prevalence of diabetes mellitus in a Nigerian population. Trans Roy Soc Trop Med & Hyg. 83: 417-418

Erasmus RT, Blanco Blanco EV, Okesina AB, Gqweta Z, Matsha T. 1999a. Assessment of glycaemic control in stable type 2 black South African diabetics attending a peri-urban clinic. Postgrad Med J. 75(888):603-606.

Erasmus R T, Blanco E, Okesina. 1999b. Hypertension, proteinuria and renal insufficiency in black South Africans with non-insulin dependent diabetes. Diabetes International 9(3), 66-69.

Erasmus RT, Blanco-Blanco EV. 2000. Standards of care of diabetic patients at a peri-urban hospital in the Eastern Cape. SA F Pract 22(31)17 -20.

Erasmus RT, Blanco-Blanco E, Okesina AB, Matsha T, Gqweta Z, Mesa JA. 2001a. Prevalence of diabetes mellitus and impaired glucose tolerance in factory workers from Transkei, South Africa. S Afr Med J. 91:157-160.

42 Erasmus RT, Blanco-Blanco E, Okesina AB, Mesa Arana J, Gqweta Z, Matsha T. 2001b. Importance of family history in type 2 black South African diabetic patients. Postgrad Med J 77:323-325.

European Diabetes Epidemiology Group. 1999. Is fasting glucose sufficient to define diabetes? Epidemiological data from 20 European studies. The DECODE-study group. Diabetes Epidemiology: Collaborative analysis of Diagnostic Criteria in Europe. Diabetologia 42(6):647-54

Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. 1997. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 20:1183–1197.

Flyvbjerg A, Goldstein BJ (Eds). 2010. Textbook of Diabetes. Chapter 1. Diabetes in its Historical and Social context. 5th Ed. Wiley-Blackwell.

Friis-Moller N, Weber R, Reiss P, Thiebaut R, Kirk O, d’Arminio Monforte A, Pradier C, Morfeldt L, Mateu S, Law M, El-Sadr W, De Wit S, Sabin CA, Phillips AN, Lundgren JD. 2003. Cardiovascular disease risk factors in HIV patients. Association with antiretroviral therapy. Results from the DAD study. AIDS 17:1179-93.

Fung TT, McCullough M, van Dam RM, Hu FB. 2007. A prospective study of overall diet quality and risk of type 2 diabetes in women. Diabetes Care 30:1753-1757.

Garg JP, Bakris GL. 2002. Microalbuminuria: marker of vascular dysfunction, risk factor for cardiovascular disease. Vasc Med 7:35–43.

Genuth S, Alberti KG, Bennett P, Buse J, Defronzo R, Kahn R, Kitzmiller J, Knowler WC, Lebovitz H, Lernmark A, Nathan D, Palmer J, Rizza R, Saudek C, Shaw J, Steffes M, Stern M, Tuomilehto J, Zimmet P. Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. 2003. Follow- up report on the diagnosis of diabetes mellitus. Diabetes Care 26:3160-3167.

Gill GV, Hyddle KR, Rolfe M. 1995. Mortality and outcome of insulin-dependent diabetes in Soweto, South Africa. Diabet Med 12:546-550.

Glass TR, Ungsedhapand C, Wolbers M, Weber R, Vernazza PL, Rickenbach M, Furrer H, Bernasconi E, Cavassini M, Hirschel B, Battegay M, Bucher HC. 2006. Prevalence of risk factors for cardiovascular disease in HIV-infected patients over time: the Swiss HIV Cohort Study. HIV Med 7:404-10.

Goedecke JH, Jennings CL, Lambert EV. 2005. Obesity in South Africa. Chron Dis lifestyle S A 7: 65- 73.

Goldhaber-Fiebert JD, Jeon CY, Cohen T, Murray MB. 2011. Diabetes mellitus and tuberculosis in countries with high tuberculosis burdens: individual risks and social determinants. Int J Epidemiol 40 (2): 417-428.

43 Gonen B, Rachman H, Rubenstein AH, Tanega SP, Horwitz DL: 1977. Hemoglobin A1c as an indicator of the degree of glucose intolerance in diabetics. Lancet 2:734–737.

Gomez-Perez FJ, Aguilar-Salinas CA, Lopez-Alvarenga JC, Guillen LE, Wong B, Rull JA. 1998. Lack of agreement between the World Health Organization category of impaired glucose tolerance and the American Diabetes Association category of impaired fasting glucose. Diabetes Care 21: 1886– 1888.

Hall V, Thomsen RW, Henriksen O, Lohse N. 2011. Diabetes in Sub Saharan Africa 1999-2011: epidemiology and public health implications. A systematic review. BMC Public Health 11:564.

Herman WH, Hoerger TJ, Brandle M, Hicks K, Sorensen S, Zhang P, Hamman RF, Ackermann RT, Engelgau MM, Ratner RE. 2005. The cost-effectiveness of lifestyle modification or metformin in preventing type 2 diabetes in adults with impaired glucose tolerance. Ann Intern Med 142: 323– 332.

Hitman GA, McCarthy MI. 1991. Genetics of non-insulin dependent diabetes mellitus. Baillieres Clin Endocrinol Metab 5:477–93.

Holt RIG, Cockram C, Flyvbjerg A, Goldstein BJ (Eds) 2010. Textbook of Diabetes. Chapter 1. Diabetes in its Historical and Social context. 5th Ed. Wiley-Blackwell.

International Diabetes Federation. 2011. IDF Diabetes Atlas, 5th ed. Brussels, Belgium: International Diabetes Federation, Available at www.idf.org/diabetesatlas/.

Jamison DT, Breman JG, Measham AR, Alleyne G, Claeson M, Evans DB, Jha P. Mills A, Musgrove P. (Eds). 2006. Disease control priorities in developing countries. 2nd ed. New York, NY, Oxford University Press.

Javitt JC, Aiello LP. 1996. Cost-effectiveness of detecting and treating diabetic retinopathy. Ann Intern Med 124 (1 pt 2):164–169.

Joshi N, Caputo GM, Weitekamp MR, Karchmer AW. 1999. Infections in patients with diabetes mellitus. N Engl J Med 341: 1906–1912.

Katahira M. 2009 A Proposal for a New Classification of Type 1 Diabetes Mellitus Based on clinical and Immunological Evidence. Recent Patents on Endocrine, Metabolic & Immune Drug Discovery. 3, 54-59.

Kengne AP, Amoah AG, Mbanya JC. 2005. Cardiovascular complications of diabetes mellitus in sub- Saharan Africa. Circulation 112: 3592–601.

44 King H, Aubert R, Herman W. 1998. Global burden of diabetes, 1995-2025. Prevalence, numerical estimates and projections. Diabetes Care 21, 1414-1431.

King H, Rewers M. 1991. Diabetes in adults is now a Third World Problem. Bull World Health Org 6, 543-548.

King H, Rewers M. 1993. WHO Ad Hoc Diabetes Reporting Group: Global estimates for prevalence of diabetes and impaired glucose tolerance in adults. Diabetes Care 16:157-177.

Kissebah AH, Krakower GR. 1994. Regional adiposity and morbidity. Physiol Rev. 74:761-811.

Kitabchi AE, Umpierrez GE, Murphy MB, Barrett EJ, Kreisberg RA, Malone JI, Wall BM. 2001. Management of hyperglycaemic crises in patients with diabetes. Diabetes Care 24:131-153.

Klein B, Klein R, Moss S, Cruickshanks KJ. 1996. Parental history of diabetes in a population based study. Diabetes Care 19:827-30.

Ko GT, Chan JC, Woo J, Cockram CS. 1998. Use of the 1997 American Diabetes Association diagnostic criteria for diabetes in a Hong Kong Chinese population. Diabetes Care 21(12):2094-7.

Ko SH, Lee WY, Lee JH, Kwon HS, Lee JM, Kim SR, Moon SD, Song KH, Han JH, Ahn YB, Yoo SJ, Son HY. 2005. Clinical characteristics of diabetic ketoacidosis in Korea over the past two decades. Diabet Med 22:466-469.

Laaksonen DE, Lakka TA, Myyssonen K, Rissanen T, Niskanen LK, Salonen JT. 2002. Serum fatty acid composition predicts development of impaired fasting glycaemia and diabetes in middle-aged men. Diabetes Med 19, 456–464.

Leung CC, Lam TH, Chan WM, Yew WW, Ho KS, Leung GM, Law WS, Tam CM, Chan CK, Chang KC. 2008. Diabetic control and risk of tuberculosis: a cohort study. Am J Epidemiol 167 (12): 1486- 1494.

Levetan BN, Levitt NS, Bonnici F. 1997. Hyperglycaemic emergencies are a common problem. S Afr Med J 87:368-370.

Levitt NS, Bradshaw D, Zwarenstein MF, Bawa AA, Maphumolo S. 1997. Audit of public sector primary diabetes care in Cape Town, South Africa: high prevalence of complications, uncontrolled hyperglycaemia, and hypertension. Diabet Med 14: 1073–7.

Levitt NS, Bradshaw D. 2006. The impact of HIV/AIDS on Type 2 diabetes prevalence and diabetes healthcare needs in South Africa: projections for 2010. Diabet Med 23:103-104

Levitt NS, Katzenellenbogen JM, Bradshaw D, Hoffman MN, Bonnici F. 1993. The prevalence and identification of risk factors for NIDDM in urban Africans in Cape Town, South Africa. Diabetes Care 16: 601–607. 45 Levitt NS, Steyn K, Lambert EV, Reagon G, Lombard CJ, Fourie JM, Rossouw K, Hoffman M. 1999. Modifiable risk factors for Type 2 diabetes mellitus in a peri-urban community in South Africa. Diabet Med 16:946-950.

Levitt NS. 2008. Diabetes in Africa: epidemiology, management and healthcare challenges. Heart 94(11):1376-82.

Loock M, Steyn K, Becker P, Fourie J. 2006. Coronary heart disease and risk factors in black South Africans– a case-control study. Ethn Dis 16(4):872-9.

MacIsaac RJ, Lee LY, Mcneil KJ, Tsalmandris C, Jerums G. 2002. Influence of age on the presentation and outcome of acidosis and hyperosmolar diabetic emergencies. Intern Med J 32:379-385.

Mash B, Levitt NS. 1999. Quality improvement in the care of people with diabetes in Khayelitsha, Cape Town. S A Fam Pract 20 (1): 123-125.

Mbanya JC, Motala AA, Sobngwi E, Assah FK, Enoru ST. 2010. Diabetes in sub-Saharan Africa. The Lancet (375) 26, 2254-66.

Mbanya JC, Sobngwi E, Mbanya D. 2001. HLA-DRB1, -DQA1, -DQB1 and DPB1 susceptibility. Eur J Immunogenet 28: 459–62

Mbanya JC, Sobngwi E. 2003. Diabetes microvascular and macrovascular disease in Africa. J Cardiovasc Risk 10: 97–102.

McLarty DG, Kinabo L, Swai ABN. 1990. Diabetes in tropical Africa: a prospective study, 1981–7. II Course and prognosis. BMJ 300:1107–10.

McLarty DG, Swai AB, Kitange HM, Masuki G, Mtinangi BL, Kilima PM, Makene WJ, Chuwa LM, Alberti KG. 1989. Prevalence of diabetes and impaired glucose tolerance in rural Tanzania. Lancet 871- 874.

Mdubeki N, Blanco-Blanco E, Erasmus RT. 2001. The dietary pattern of black African diabetic patients attending a tertiary care clinic in the Eastern Cape. JEMDSA 2001, (6):1, 44.

Mennen LI, Jackson M, Sharma S, Mbanya JC, Cade J, Walker S, Riste L, Wilks R, Forrester T, Balkau B, Cruickshank K. 2001. Habitual diet in four populations of African origin: a descriptive paper on nutrient intakes in rural and urban Cameroon, Jamaica and Caribbean migrants in Britain. Public Health Nutr 4: 765-72.

Mhando PA, Yudkin JS. 1980. The pattern of diabetic complications in African patients in Dar es Salaam. Trop Geogr Med 32, (4): 317-23.

46 Mollentze WF, Moore AJ, Steyn AF, Joubert G, Steyn K, Oosthuizen GM, Weich DJ. 1995. Coronary heart disease risk factors in a rural and urban Orange Free State black population. S Afr Med J 85: 9096.

Motala AA, Esterhuizen T, Gouws E, Pirie FJ, Omar MA. 2008. Diabetes mellitus and other disorders of glycaemia in a rural South Africa community: prevalence and associated risk factors. Diabetes Care 31: 1783-88.

Motala AA, Pirie FJ, Gouws E, Amod A, Omar MA. 2001. Microvascular complications in South African patients with long-duration diabetes mellitus. S Afr Med J 91:987-992.

Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ. 2008. Translating the A1c assay into estimated average glucose values. Diabetes Care. 31:1473-1478.

National Diabetes Data Group. 1979. Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes 28:1039-1057.

Nelson RG, Pettitt DG, Carrher MJ, Baird HR, Knowler WC. 1988. Effect of proteinuria on mortality in NIDDM. Diabetes 37: 1499.

Newman B, Selby JV, King MC, Slemenda C, Fabsitz R, Friedman GD. 1987. Concordance for type 2 diabetes mellitus in male twins. Diabetologia 30:763–8.

Nyenwe E, Loganathan R, Blum S, Ezuteh D, Erani D, Palace M, Ogugua C. 2007. Admissions for diabetic ketoacidosis in ethnic minority groups in a city hospital. Metabolism 56:172-178.

Okoro EO, Yusuf M, Salawu HO, Oyejola BA. 2007. Outcome of diabetic hyperglycaemic emergencies in a Nigerian cohort. Journal of Chinese Clinical Medicine 2: 77-82.

Omar M, Seedat M, Motala A, Dyer R, Becker P. 1993. The prevalence of diabetes mellitus and impaired glucose tolerance in a group of urban South African blacks, SAMJ 83 641-643.

Omar MAK, Seedat MA, Motala AA, Dyer RB, Becker P. 1993. The prevalence of diabetes mellitus and impaired glucose tolerance in a group of urban South African Blacks. S Afr Med J 83: 641–43.

Osei K, Schuster DP, Amoah AG, Owusu SK. 2003. Diabetes in Africa: pathogenesis of type 1 and type 2 diabetes mellitus in sub-Saharan Africa-implications for transitional populations. J Cardiovasc Risk 10: 85–96

Ottmani SE, Murray MB, Jeon CY, Baker MA, Kapur A, Lönnroth K, Harries AD. 2010. Consultation meeting on tuberculosis and diabetes mellitus: meeting summary and recommendations. Int J Tuberc Lung Dis 14 (12): 1513-1517.

47 Panz VR, Joffe IB. 1999. Impact of HIV infection and AIDS on the prevalence of type 2 diabetes in South Africa in 2010. BMJ 318:1351A

Parillo M, Riccardi G. 2004. Diet composition and the risk of type 2 diabetes: epidemiological and clinical evidence. Br J Nutr 92:7-19.

Peek ME, Cargill A, Huang ES. 2007. Diabetes Health Disparities: A Systematic Review of Health Care Interventions. Med Care Res Rev. 64(5 Suppl): 101S–156S.

Permutt MA. 1990. Genetics of NIDDM. Diabetes Care 13: 1150-3.

Pirie FJ, Pegoraro R, Motala AA, Rauff S, Rom L, Govender T, Esterhuizen TM. 2005. Toll-like receptor 3 gene polymorphisms in South African blacks with type 1 diabetes. Tissue Antigens 66: 125-30

Renzaho AMN. 2004. Fat, rich and beautiful: changing socio-cultural paradigms associated with obesity risk, nutritional status and refugee children from sub-Saharan Africa. Health and Place 10(1):105-113.

Rolfe M. 1988. Diabetic eye disease in Central Africa. Diabetologia 31:88–92.

Rose M, Burkert U, Scholler G, Schirop T, Danzer G, Klapp BF. 1998. Determinants of quality of life of patients with diabetes under intensified insulin therapy. Diabetes Care 21: 1876-1883.

Rubin RR, Peyrot M, Saudek CD. 1989. Effect of diabetes education on self-care, metabolic control and emotional well-being. Diabetes Care 12: 673- 79.

Rubin RR, Peyrot M, Saudek CD. 1991. Differential effect of diabetes education on self-regulation and life style behaviors. Diabetes Care, 14: 335- 38.

Rubin RR, Peyrot M. 1999. Quality of Life and Diabetes. Diabetes Metab Res Rev 15: 205-218.

Santiago JV. 1993. Lessons from the Diabetes Control and Complications Trial. Diabetes 42: 1549- 54.

Shah BR, Hux JE. 2003. Quantifying the risk of infectious diseases for people with diabetes. Diabetes Care 26:510-513.

Shaw JE, de Courten M, Boyko EJ, Zimmet PZ. 1999. The impact on different populations of new diagnostic criteria for diabetes. Diabetes Care 22:762-766.

Shaw JE, Sicree RA, Zimmet PZ. 2010. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 87(1):4-14. 48 Simmons RK, Griffin SJ, Wareham NJ. 2007. Researching how to realize the potential of diabetes prevention. Diabet Med 24(10):1055-7.

Simpson N. 1968. Diabetes in the families of diabetics. Can Med Assoc J 98:427-32.

Small M, Alzard A, Maccuish AC. 1988. Diabetic hyperosmolar non-ketotic decompensation. Q J Med 25:251-257.

Smith CJ, Levy I, Sabin CA, Kaya E, Johnson MA, Lipman MC. 2004. Cardiovascular disease risk factors and antiretroviral therapy in an HIV-positive UK population. HIV Med 5:88-92.

Steyn K, Fourie J, Temple N (Eds). 2006. Chronic Diseases of Lifestyle in South Africa: 1995 - 2005. “Chapter 10. Diabetes mellitus and impaired glucose tolerance in South Africa by Mollentze WF & Levitt N. Technical Report. Cape Town: South African Medical Research Council.

Steyn K, Sliwa-Hahnle K, Hawkens S, Commerford P, Onin C, Ounpuu S, Yusuf S. 2005. Risk factors associated with Myocardial Infarction in Africa. The INTERHEART Africa Study. Circulation 112:3554- 3561.

Storlien LH, Baur LA, Kriketors AD, Pan DA, Cooney GJ, Jenkins AB, Calvert GD & Campbell LV. 1996. Dietary fats and insulin action. Diabetologia 39 621–631.

Surka J, Erasmus RT, Blanco-Blanco E, Salazar C, Okesina AB. 2001. Prevalence of diabetic retinopathy in black south African diabetics attending a tertiary clinic in the eastern cape. JEMDSA, Vol. 6 (1), 40.

The Diabetes Control and Complications Trial Research Group (DCCT). 1995. The relationship of glycemic exposure (HbA1c) to the risk of development and progression of retinopathy in the Diabetes Control and Complications Trial. Diabetes 44(8):968-983.

The Expert Committee on Diagnosis and Classification of Diabetes Mellitus. 1997. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 20:1183- 1197.

The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. 2003. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 26:3160-3167.

Tibazarwa K, Ntyintyane L, Sliwa K, Gerntholtz T, Carrington M, Wilkinson D, Stewart S. 2009. A time bomb of cardiovascular risk factors in South Africa: results from the Heart of Soweto Study ‘Heart Awareness Days’. Int J Cardiol 132(2):233-9.

49 Tien PC, Schneider MF, Cole SR, Levine AM, Cohen M, DeHovitz J, Young M, Justman JE. 2007. Antiretroviral therapy exposure and incidence of diabetes mellitus in the Women’s Interagency HIV Study. AIDS 21(13):1739-1745.

Trief PM, Grant W, Elbert K, Weinstock RS. 1998. Family environment, glycemic control, and the psychosocial adaptation of adults with diabetes. Diabetes Care 21: 241-245.

Turner R, Hattersley A, Cook J. 1992. Type 2 diabetes: search for primary defects. Ann Intern Med 24:511-16.

Unwin N, Setel P, Rashid S, Mugusi F, Mbanya JC, Kitange H, Hayes L, Edwards R, Aspray T, Alberti KGMM. 2001. Non-communicable diseases in sub-Saharan Africa: where do they feature in the health research agenda? Bull World Health Organ 79: 947–953.

US Department of Health and Human Services. Health United States, 1990. 1991. Public Health Service Center for Disease Control. National Center for Health Statistics, DHHS no PHS 91-1232.

Van Zyl Smit RE, Burch VC, Willcox PA. 2007. The provision of appropriate critical care services in secondary level hospitals in South Africa. S Afr Med J 97:270-272.

Vorster HH, Venter CS, Wissing MP, Margetts BM. 2005. The nutrition and health transition in the North West Province of South Africa: a review of the THUSA (Transition and Health during Urbanisation of South Africans) study. Public Health Nutr 8: 480-90.

Wachtel TJ, Tetu-Mouradjian LM, Goldman DL, Ellis SE, O’Sullivan PS. 1991. Hyperosmolarity and acidosis in diabetes mellitus; a three-year experience in Rhode Island. J Gen Intern Med 6:495- 502.

Wang L, Folsom AR, Zheng Z-J, Pankow JS, Eckfeldt JH. 2003. Plasma fatty acid composition and incidence of diabetes in middle-aged adults: the Atherosclerosis Risk in Communities (ARIC) Study. Am J Clin Nutr 78, 91–98.

Wayne C. 1988. Why not care for your diabetic patients? London: Royal College of General Practitioners.

Wild S, Roglic G, Green A, Sicree R, King H. 2004. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030, Diabetes Care 27 (5) 1047-1053.

World Health Organization. 1990. Diet, Nutrition, and the Prevention of Chronic Diseases. Report of a WHO Study Group. Geneva: WHO. (WHO Technical Report Series No. 797).

World Health Organization. 1994. Prevention of diabetes mellitus. Report of a WHO Study Group. Geneva: World Health Organization. No. 844. Available at http://www.idf.org/diabetesatlas

World Health Organization. 1997. Non-communicable Disease Prevention and Control: Report by the Director-General EB101/14. Geneva, World Health Organization. 50 World Health Organization. 1999. Definition, Diagnosis and Classification of Diabetes Mellitus and its Complications. Report of a WHO Consultation. Geneva: World Health Organization.

World Health Organization. 2006. Definition and diagnosis of diabetes mellitus and intermediate hyperglycemia. Report of a WHO/IDF Consultation. World Health Organization Press. Geneva. Switzerland. Available at http://www.who.int/diabetes/publications/diagnosis_diabetes2006/en/ index.html

World Health Organization. 2011. Global status report on non-communicable diseases 2011. WHO, Geneva, Switzerland. Available on the WHO web site (www.who.int).

World Health Organization. 2011. Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus. Abbreviated report of a WHO consultation, Geneva, Switzerland. Available on the WHO web site (www.who.int) WHO/NMH/CHP/CPM/11.1.

Zimmet P. 1999. Diabetes epidemiology as a trigger to diabetes research. Diabetologia 42: 499- 518.

Zouvanis M, Pieterse AC, Seftel H, Joffe B. 1997. Clinical characteristics and outcome of hyperglycaemic emergencies in Johannesburg Africans. Diabet Med 14:603-606.

51 52 ACKNOWLEDGEMENTS “When you practice gratefulness, there is a sense of respect towards others” The Dalai Lama

I would like to express my gratitude to the Walter Sisulu University for providing me the opportunity to develop myself as an educationalist, a researcher and a medical consultant.

I am also thankfulness to the WSU community, staff and students, for the vast experiences that have enriched my life during all academic and non-academic interactions.

I would like to thank the Umtata Academic Hospital Complex; the management and staff for supporting and enabling our research intentions. Special thanks to the nursing staff of diabetic clinic at UGH and the department of Internal Medicine for the enthusiastic engagement in research collaborations with our department during these many years. It is also imperative that I indicate my gratitude to the Pathology Laboratory staff and the National Health Laboratory Services (NHLS) management for their consistent cooperation and support to my research and service endeavours during all these years.

I would like to show my gratitude to the community members and diabetic patients from Umtata and its surrounding areas for welcoming us, cooperating and enabling the successful completion of our projects.

I am truly indebted and grateful to the management, colleagues and support staff in the Faculty of Health Sciences. My special acknowledgments to the support and trust I received all these years from Prof. L. Mazwai, Prof. J. Surka, Prof. Mfenyana, Prof. J. Iputo and Prof. N. Sokhela.

I owe sincere and earnest thankfulness to all my research co-workers more especially the UNITRA/ WSU chemical pathology staff especially Prof. RT Erasmus, Prof. T. Matsha, Mr Z. Gqweta, for being exceptional team-players, and to Dr Chukwuma Ekpebegh for his, also exceptional, collaborative research inquisitiveness.

I am deeply obliged to acknowledge some of my colleagues, who nourished me all these years not only with inspiration, encouragement and faith but also with the wisdom of their expertise, most especially to Prof. A. Stepien, Prof. R.T. Erasmus, Prof. E.N. Kwizera and Prof. H. Vermaak.

This inaugural lecture would not have been possible without the outstanding support provided by the WSU Research Directorate particularly Dr E. Cishe and Ms. N. Sigodi.

It is a great pleasure to thank everyone who helped me during the preparation of this lecture, especially Prof A. Awotedu and Prof. Mayra Gari for their kind and wise contributions, Ms. Louise Roberts for going the extra mile in the revision of this document, Mr Steyn Swanepoel for his always- available resourceful help and to Dr Charles Drake for his relieving support all this time.

I am also pleased to give a special recognition to my Cuban colleagues and friends who, during all these years I have been in South Africa, have also supported me as if they were my own family.

I dedicate a big “thank you!” to the many educators who have contributed to my progress throughout my life.

53 My deepest gratefulness is also conveyed to my family, especially my parents and siblings, for nurturing the essence of who I am today.

Last but not least, my genuine appreciation to my wife Prof. Mirta Garcia-Jardon, for being the full complement of my life and my career, and to my son Ernesto Blanco-Garcia for being awesome and making me proud.

I thank you all!

54 Citation

Prof. Ernesto Virgilio Blanco-Blanco was born in Havana City, Cuba, in 1965. He is the fifth born of six siblings. His father, Virgilio Blanco-Prado was late in 2007 and his mother Georgina Blanco-Manso is still alive. He has been married to Prof Mirta Garcia-Jardon with whom he has a 21-year-old son, Ernesto Blanco-Garcia.

Upon completing his high school studies, in 1983, he registered with the Medical School at the University of Havana where he qualified as a Medical Doctor in August 1989.

In September 1989 he was admitted into a nationally prioritized specialization program also with the University of Havana and after 4 years of registrar training, in May 1994, he qualified as First Degree Specialist in Clinical Laboratory (known as Clinical Pathology in South Africa) with the research mini- dissertation entitled: “Epidemiology and Laboratory features of the Monoclonal Gammapathies in the elderly”. He then joined the Medical Laboratory Services at the Academic Hospital “10 de Octubre” in Havana as specialist consultant until July 1994 when he was appointed Head of Laboratory Services at the same institution.

In 2002, after completing the required exercises by the national accreditation bodies and the dissertation topic “Pathophysiology of Diabetes mellitus” he qualified as Second Degree Specialist in Clinical Laboratory. In 2008, he also completed the MSc in Infectious Diseases with the research report on “Laboratory diagnosis of TB meningitis”.

Professor Blanco-Blanco joined the University of Transkei (UNITRA) teaching community in 1998 as lecturer in Chemical Pathology. He was promoted to senior lecturer in 2005 and then to his current position of Professor and Head in 2007 up to date. He has been Consultant Chemical Pathologist at Umtata Academic Hospital since 1998 when he continued to provide the service as consultant and academic head for the Chemical Pathology Service at the Nelson Mandela Tertiary Laboratory under the National Health Laboratory Services (NHLS). He also represents the Eastern Cape and the Walter Sisulu University (WSU) in the National Chemical Pathology Experts Committee.

He has presented more than 100 papers in local and international conferences, and has more than 30 papers published in national and international journals. Besides his first line research on diabetes mellitus, Prof. Blanco’s contribution also involves general pathology as well as health sciences education. He is currently completing his research report as a postgraduate student for the MPhil in Health Sciences Education with the University of Stellenbosch on the topic “MBChB students’ perceptions on feedback during PBL tutorials”.

Prof. Blanco is passionate about teaching, he was instrumental to the introduction of Chemical Pathology to the Integrated Pathology courses under the PBL at WSU as well as to the implementation of the post-graduate courses in chemical pathology (Post-Graduate Diploma and MSc in Chemical Pathology) in WSU in 2009, with more than 10 graduates in these courses. He has supervised numerous MSc students in the completion of their research output both in Cuban and South African programs and he has served as external examiner for the MSc Chemical Pathology program at the Cape Peninsula University of Technology.

He is engaged in the Faculty of Health Sciences Committees where he has chaired the Curriculum Development Committee and he currently chairs the Resources Development and Library Information Services Committees.

55 Prof Blanco is also member of the South African Society of Diabetes Educators; Society of Endocrinology, Metabolism and Diabetes of South Africa; South African Association of Clinical Biochemistry; South African Association of Medical Educators and Cuban Society of Clinical Pathology.

His collaboration with other departments within the FHS; with the FSET is well known; as well as his extended contribution to the clinical departments and clinical teaching in most of the laboratory fields.

56 57 58 59 Design: Mthatha Health Resource Centre 60