Context for improving access to care for children and youth with diabetes in less- resourced countries.

Graham David OGLE ORCID 0000-0002-2022-0866

Doctor of Medical Science June 2020 Faculty of Medicine, Dentistry and Health Sciences

Submitted in total fulfilment of the requirements for the degree of Doctor of Medical Science at the University of Melbourne by compilation of published papers.

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1.0 THESIS ABSTRACT

There are major deficits in knowledge related to the epidemiology and care of the various types of diabetes in young people in less-resourced countries. Multiple barriers exist at individual, community, health system, national, and international levels that must be overcome to lessen the gap in outcomes between advantaged and disadvantaged regions. This thesis presents 11 published papers by the candidate addressing this gap in knowledge. Type 1 diabetes (T1D) incidence data is presented for three countries with no previous data (Fiji, Bolivia and Azerbaijan), showing differing rates in each country, and in Fiji differing rates in the two main ethnic populations. Novel information on the types of diabetes is presented for Azerbaijan (along with the incidence data aforementioned), and Bangladesh. Results in Azerbaijan were similar to those seen in European populations. In Pakistan and Bangladesh, it is common to see atypical forms that clinically present like T1D cases but do not have low C-peptide values or diabetes autoantibodies. Five papers examine costs and access to care. In a survey of 71 countries, availability of nearly all key components of care was greatly reduced in lower-income countries. A study of costs to families in 15 countries demonstrated that the cost of core supplies is prohibitively expensive for many families. A comprehensive review of issues surrounding access to supplies for self-monitoring of blood glucose presents new information on the global market and makes numerous practical recommendations. Progress towards Universal Health Coverage for provision of insulin and blood glucose test strips was evaluated in 44 countries, showing that there was greater progress for insulin than for test strips. A novel framework for describing T1D care levels (Basic, Intermediate and Comprehensive) provides a way of identifying the steps required to improve care in a particular situation, and the data presented from Bolivia shows that Intermediate Care can achieve outcomes similar to those in some highly-resourced countries. The final paper, using robust, novel and replicable methodology, demonstrates the efficacy of traditional evaporative cooling devices used for insulin storage where refrigerators are not available. In conclusion, efforts to improve care for young people with diabetes in less-resourced countries must take into account wide differences in incidence and the types of diabetes that occur between countries. Furthermore, for care to improve, many components of care need to be addressed. The concept of ‘Intermediate Care’ provides an achievable level of care that can result in reasonable outcomes even in poorly resourced health systems.

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2.0 DECLARATION

This is to certify that:

1. The thesis comprises only my original work towards the Doctor of Medical Science, except where indicated in the Preface.

2. Due acknowledgement has been made in the text to all other material used.

3. This thesis is less than 100,000 words in length, exclusive of bibliographies and appendices.

Signed: Graham David Ogle

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3.0 PREFACE

This compilation of published manuscripts is submitted for examination as a basis for being awarded a Doctor of Medical Science by publication / compilation of papers. The 11 papers listed on pages 6-7 which form the body of results of this thesis could not have been completed without the efforts, dedication, and support of numerous colleagues. However, I can confidently say that, for all of these papers, I initiated and developed the respective study concepts and designs, and was the main writer of every manuscript. I was also the main person involved in the respective ethics approvals, data compilation and analysis, writing, submission for publication, and revisions as required by reviewers. All co-authors have authorised that I contributed at least 50% of the content and was the primary author. The research was undertaken while I was the General Manager of the Life for a Child Program (LFAC), based at Diabetes NSW in Sydney. I thank all the collaborators in many countries who contributed to this body of work. In particular, for Papers 1-5, I thank the lead investigators in each country: Dr Rigamoto Taito (Fiji), Dr Gunduz Ahmadov (Azerbaijan), Dr Elizabeth Duarte (Bolivia), Asher Fawwad (Pakistan), and Dr Bedowra Zabeen (Bangladesh), along with the overseas research institute collaborators: Dr Janelle Noble, Dr Steven Mack, and Julie Lane who did the HLA analysis at Children’s Hospital Oakland Research Institute in California, and Dr Mark Atkinson and Clive Wasserfall (University of Florida) who provided guidance on diabetes autoantibodies and C-peptide studies. Under my supervision, Melinda Morrison (Diabetes NSW) made a substantial contribution to the analysis of the Fiji study (Paper 1); Gabriel Gregory (medical student, University of Sydney) conducted the analysis of the Bolivia study (Paper 2); and Denira Govender (medical student, University of Sydney) conducted the analysis on the data from Azerbaijan, Pakistan, and Bangladesh (Papers 3-5). I also thank Gabriel Gregory for his outstanding work in developing the mathematical model that we have subsequently used to explore the cost- effectiveness and other outcomes of the ‘Intermediate Care’ concept (see Section 11.3). For Papers 5-10, in particular for their contributions I thank Prof. Martin Silink (Chairman of LFAC until 2018), Angela Middlehurst (LFAC Education Manager until 2018), and Emma Klatman (LFAC Heath Systems Specialist), as well as Prof. Alicia Jenkins (Universities of Sydney and Melbourne), Prof. Martin McKee (London School of Hygiene and Tropical Medicine), Prof. Yakoob Ahmedani (Baqai Institute of Diabetes and Endocrinology, Pakistan), Dr Julia von Oettingen (McGill University, Canada), and Dr Ragnar Hanas (University of Gothenburg, Sweden). I would like to make a particular acknowledgement to Emma Klatman for conceiving the triangle-shaped visualisation to represent the three dimensions of the WHO’s ‘Fair Choices on the Path to Universal Health Coverage’ paradigm. With respect to Paper 11 – the ‘Clay Pot Study’, I would particularly like to acknowledge the idea of David Mason (health studies student, Macquarie University) to consider the effects of humidity, Dr Andrzej Januszewski for the idea to use cluster analysis, all the partner centres for donating devices, and particularly Michael Kriegbaum Skjødt (Denmark) for accepting my invitation to travel to Khartoum to conduct the study with Dr Mohamed Abdullah. Michael would have been a co-author on this paper, but he withdrew his name on his own volition after the paper had been accepted, as he had just started working with a major insulin manufacturer.

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No third-party editorial assistance was provided in preparation of the thesis.

The eleven papers included in the thesis are all accepted and published:

1. Ogle GD, Morrison MK, Silink M, Taito RS. Incidence and prevalence of diabetes in children aged <15 years in Fiji, 2001-2012. Pediatric Diabetes 2016: 17: 222–226. Accepted 19th January, 2015, published May 2016.

2. Duarte Gómez E, Gregory GA, Castrati Nostas M, Middlehurst AC, Jenkins AJ, Ogle GD. Incidence and mortality rates and clinical characteristics of type 1 diabetes among children and young adults in Cochabamba, Bolivia. J Diabetes Res 2017; 8454757. Accepted 29th August, 2017, published Aug 2017.

3. Ahmadov GA, Govender D, Atkinson MA, Sultanova RA, Eubova AA, Wasserfall CH, Mack SJ, Lane JA, Noble JA, Ogle GD. Epidemiology of childhood-onset type 1 diabetes in Azerbaijan: incidence, clinical features, biochemistry, and HLA-DRB1 status. Diabetes Res Clin Pract 2018:144:252-259. Accepted 13th September 2018, published Oct 2018.

4. Fawwad A, Govender D, Ahmedani MY, Basit A, Lane JA, Mack SJ, Atkinson MA, Wasserfall CH, Ogle GD, Noble JA. Clinical features, biochemistry and HLA-DRB1 status in youth-onset type 1 diabetes in Pakistan. Diabetes Res Clin Pract 2019;149:9-17. Accepted 30th January 2019, published March 2019.

5. Zabeen B, Govender G, Hassan Z, Noble JA, Lane JA, Mack SJ, Atkinson MA, Azad K, Wasserfall CH, Ogle GD. Clinical features, biochemistry and HLA-DRB1 status in youth- onset type 1 diabetes in Dhaka, Bangladesh. Diabetes Research Clinical Practice 2019;158:107894. Accepted 24th October 2019, published December 2019.

6. Ogle GD, Middlehurst AC, Silink M. The IDF Life for a Child Program Index of diabetes care for children and youth. Pediatr Diabetes 2016: 17: 374–384. Accepted 8th July 2015, published August 2016.

7. Klatman EL, McKee M, Ogle GD. Documenting and visualising progress towards universal health coverage for people with type 1 diabetes. Diabetic Res Clin Pract 2019;157:107859. Accepted 20th September 2019, published November 2019.

8. Ogle GD, Kim H, Middlehurst AC, Silink M, Jenkins AJ. Financial costs for families of children with Type 1 diabetes in lower-income countries. Diabet Med. 2016;33:820-826. Accepted 14th November, 2015, published June 2016.

9. Klatman EL, Jenkins AJ, Ahmedani Y, Ogle GD. Access to blood glucose meters and strips in less-resourced countries. Lancet Diabetes & Endocrinology. Lancet Diabetes & Endocrinology 2019;7:150-160. Accepted 30th July, 2018, published February 2019.

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10. Ogle GD, von Oettingen JE, Middlehurst AC, Hanas R, Orchard T. Levels of type 1 diabetes care in children and adolescents for countries at varying resource levels. Pediatric Diabetes. 2019;20:95-98. Accepted 10th October, 2018, published February 2019.

11. Ogle GD, Abdullah M, Mason D, Januszewski A, Besançon S. Insulin storage in hot climates without refrigeration – temperature reduction efficacy of clay pots and other techniques. Diab Med 2016;33:1544-1553. Accepted 28th August, 2016, published November 2016.

During the period in which this research was conducted, I have been employed by Diabetes NSW & ACT, with my salary covered by Diabetes NSW & ACT and grants (#2016PGT1D016 and #2019PGT1D023) from the Leona M and Harry B Helmsley Charitable Trust. I have also received a scholarship to cover course fees from the NHMRC Clinical Trials Centre at the University of Sydney.

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4.0 ACKNOWLEDGEMENTS

Numerous colleagues have contributed to make this work possible, and they are acknowledged in the preface. I have been very fortunate to have had many fine mentors during my career. I would like to thank four in particular: Prof. Martin Silink invited me to work with him to plan and establish the Life for a Child Program in 2000. In the following years, Martin’s enormous clinical experience, his grand vision about building Life for a Child and broader international diabetes coalitions, his research skills in planning and writing up studies, and his consummate diplomatic skills were all invaluable to my professional development. He introduced me to many in his extraordinary international network of diabetes connections. Martin also constantly guided and inspired me to think beyond the immediate situation and instead dream and plan on what may be possible – and often was possible once we tried. Prof. Alicia Jenkins has been my key academic mentor. Alicia encouraged me to start supervising students – summer scholarship students, MD research students, and others that wanted to get involved. She arranged for me to have a Research Associate position at the NHMRC Clinical Trials Centre at the University of Sydney, and sent brilliant students and young doctors my way, and gave much valuable advice on how to work with the students and help them achieve their best. Alicia then firmly suggested I do this doctorate, which, when achieved would permit me to potentially supervise post-graduate students and apply for research funds that I currently do not qualify for. A scholarship was received from the NHMRC Clinical Trials Centre at the University of Sydney in order to cover the course fee, related travel (such as for a symposium or conference) and for purchase of a laptop. Prof. Trevor Orchard of the University of Pittsburgh has been a wonderful mentor in improving my epidemiology skills, and also helping me to develop concepts used in many of the included papers. The clinical and research efforts that he and his students (Dr Sara Marshall and others) made in Rwanda as they supported and extended the Life for a Child efforts led to many new ideas that informed this work. Trevor also made previously unpublished 30-year complications data available for the study of the cost-effectiveness and other outcomes of the ‘Intermediate Care’ concept (see Section 13.3). Finally, I thank Dr Mark Atkinson of the University of Florida. Mark is a pre-eminent T1D researcher, constantly in-demand and involved in a myriad of projects. Despite this, he has found time on countless occasions to be supportive of my research activities, offering novel suggestions and being enthusiastic about potential new collaborations. Mark introduced me to Dr Janelle Noble at Children’s Hospital Oakland Research Institute, which led to the inclusion of HLA studies, and has mobilised Dr Clive Wasserfall and others from his institution (the University of Florida) to help. I would also like to thank Diabetes NSW & ACT and the Leona M and Harry B Helmsley Charitable Trust for supporting my salary throughout this period of research.

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5.0 TABLE OF CONTENTS

1.0 Thesis Abstract 2 2.0 Declaration 3 3.0 Preface 4 4.0 Acknowledgements 7 5.0 Table of Contents 8 6.0 Introduction 9 6.1 Aims 9 6.2 Hypotheses 9 6.3 Summary of published papers 10 7.0 Literature Review 11 7.1 Incidence of type 1 diabetes in Fiji, Bolivia and Azerbaijan 11 7.2 Types of diabetes in Pakistan and Bangladesh 12 7.3 Factors hindering quality care 13 7.4 Temperature reduction efficacy of evaporative cooling devices 14 8.0 Published papers (for full titles see pages 6-7) 16 8.1 Paper 1 – Fiji 16 8.2 Paper 2 – Bolivia 25 8.3 Paper 3 – Azerbaijan 41 8.4 Paper 4- Pakistan 55 8.5 Paper 5 – Bangladesh 73 8.6 Paper 6 – Index of Diabetes Care 88 8.7 Paper 7 – Progress towards Universal Health Coverage 107 8.8 Paper 8 – Financial costs 122 8.9 Paper 9 – Blood glucose meters and strips 135 8.10 Paper 10 – Levels of Care 156 8.11 Paper 11 – Insulin storage 167 9.0 Discussion 185 9.1 Incidence 185 9.2 Types of diabetes 186 9.3 Access to care 188 9.4 Insulin storage 190 10.0 Summary and future directions 192 10.1 Incidence 192 10.2 Types of diabetes 193 10.3 Access to care 194 10.4 Insulin storage 196 11.0 Bibliography 198 12.0 Appendices 206 Appendix A PDF versions of published papers* 207-307

*These papers are third-party copyright material and so should not be included in the online version.

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6.0 INTRODUCTION

The overall goal of this thesis is to improve understanding of diabetes in young people in less- resourced countries, with specific foci on epidemiology and access to quality care. The work covers four main areas, as described in the Aims below:

6.1 AIMS

1. Provide the first data on incidence of type 1 diabetes in children in three countries: a. Fiji b. Bolivia c. Azerbaijan 2. Investigate the frequency and characteristics of ‘atypical’ forms of type 1 and other causes of diabetes in children and youth in three non-European populations: a. Azerbaijan b. Pakistan c. Bangladesh 3. Document factors hindering access to type 1 diabetes care for young people in less- resourced countries, and propose an “intermediate” care level suitable for such countries. 4. Determine the efficacy of traditional and modern evaporative cooling devices in reducing insulin storage temperatures.

6.2 HYPOTHESES

1. With respect to the incidence of type 1 diabetes in children: a. The incidence is very low in Fiji b. The incidence is very low in Bolivia c. The incidence in Azerbaijan is substantially less than that seen in populations in Western Europe 2. With respect to the frequency and characteristics of ‘atypical’ forms of type 1 and other causes of diabetes in youth: a. ‘Atypical’ forms of diabetes that are difficult to categorise are common in Pakistan and Bangladesh, but uncommon in Azerbaijan 3. With respect to factors hindering access to type 1 diabetes care in young people in less- resourced countries, and proposal of an “intermediate” care level suitable for such countries: a. There are many health system deficiencies that hinder provision of quality care to young people with diabetes in less-resourced countries, not just access to insulin. b. A holistic approach is needed to address these health system deficiencies and improve outcomes.

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c. An ‘Intermediate’ Level of Care which leads to reasonable outcomes is a realistic possibility for less-resourced countries 4. With respect to the efficacy of traditional and modern evaporative cooling devices in reducing insulin storage temperatures: a. Traditional evaporative cooling methods are efficacious in reducing insulin storage temperatures in the absence of refrigeration

6.3 SUMMARY OF INCLUDED MANUSCRIPTS

A series of 11 manuscripts in the four thematic areas of: incidence, types of diabetes, health system factors hindering access, and efficacy of evaporative cooling devices. Papers 1 (Fiji), 2 (Bolivia), and 3 (Azerbaijan) provide information on incidence of T1D in children in those countries. Papers 3 (Azerbaijan), 4 (Pakistan) and 5 (Bangladesh) describe the clinical features, biochemical markers, and HLA status of new-and recent onset cases of T1D and other types of diabetes in young people with diabetes in those countries. Papers 1 (Fiji), 2 (Bolivia), and 3 (Azerbaijan) also provide some information on types of diabetes occurring in the respective countries. Papers 6 (Index paper) and 7 (Universal Health Coverage paper) describe the deficiencies in health systems with regard to youth diabetes care in 43 and 37 less-resourced countries respectively, comparing these to high-income countries. Paper 8 gives information on out-of-pocket costs for families in 15 countries. Paper 9 provides new and collates existing information on the use of blood glucose meters and strips. Paper 10 presents a new paradigm of Levels of Care, describing an “Intermediate Level” that can achieve reasonable outcomes, as evidenced by Paper 2 (Bolivia) and other published papers. Paper 11 assesses the temperature-lowering efficacy of evaporative cooling devices.

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7.0 LITERATURE REVIEW

7.1 Incidence of diabetes in children and adolescents in less-resourced countries The great majority of cases of diabetes in children and adolescents are type 1 diabetes (T1D), although type 2 diabetes (T2D) and other types of diabetes are also seen. T1D is due to an immune-modulated destruction of pancreatic ß-cells, with both genetic and environmental factors important in pathogenesis. The genetic factors are relatively well-understood, with Human Leukocyte Antigen (HLA) haplotypes contributing 30-50% of the risk in European populations, with much smaller contributions from a number of other genes (Mayer-Davis 2018, Katsarou 2017). The environmental factors are less understood, with immune responses to particular viral infections at a particular age possibly being one of the main contributors (Mayer- Davis, 2018, Katsarou 2017, Craig 2014). T1D can occur at any age after the neonatal period, with the peak age of onset between 5 and 14 years (Writing Group 2007). Recently the proportion of cases diagnosed at <5 years of age has increased in some countries (Mayer-Davis 2018). Incidence tends to be marginally higher in boys (Mayer-Davis 2018), although in low incidence populations there is often a female preponderance (Karvonen 1997). The incidence of T1D varies markedly around the world, with the highest incidence of over 60 per 100,000 children <15 years per year in Finland, and incidences of <1/100,000 in some countries in South America and Papua New Guinea (Craig 2014, DiaMond 2006, Patterson 2019 DRCP, Ogle 2001). It is possible that reported incidence rates in some countries are underestimated due to deaths from misdiagnosis at onset (Rwiza, 1986, Atun 2017, Marshall 2013), with this issue also discussed more in Paper 6. However, it is certain that this factor does not explain all of the wide differences in incidence across the globe, as Japan, with its high- quality health system, has an incidence of only 2.25 per 100,000 (Onda 2017). High incidences are not restricted to European populations. Indeed, some countries in the Middle East and North Africa have much higher rates than most European countries: for instance Kuwait, Saudi Arabia and Qatar are amongst the 10 countries with the highest incidence, and Algeria also has a high rate (IDF 2019, Patterson 2019 (DRCP)). Incidence rates are also rising in most countries where there is adequate data, with an average increase of around 3% per year (DiaMond 2006, Patterson 2019 (Diabetologia)). Knowledge of incidence rates is important for many reasons within the country concerned, and also globally. Accurate data for a country aids appropriate health service planning and resource allocation, can identify areas where children may be dying misdiagnosed or where mortality rates in diagnosed children may be particularly high, guides teaching and training of health professionals, and is critical in effective advocacy efforts. Exploration of possible reasons for the wide range of incidences seen across the world is also important in the global understanding of diabetes as researchers work towards prediction and prevention. Since the 1980s, there have been increasing efforts to determine incidence in countries without any published data, as well as continuing existing registries in countries with data (La Porte 1985, DiaMond 2006, Patterson (Diabetologia)). Despite this, the 2019 IDF Atlas data (IDF 2019, Patterson 2019 (DRCP)) has T1D incidence data only for 94 (45%) of the world’s 211 countries. In addition, much of the Atlas data

11 is dated. The last year studied was 2010 or later in only 53 (56%) of 94 countries, and was before 2000 in 28 countries (29.8%). Furthermore, there is very sparse information from low- and lower-middle income countries. Of the 94 countries with data, 81 (86%) are high-income and upper-middle income countries. Only three (10%) of the world’s 31 low-income countries have data. For the Africa region (sub-Saharan Africa), only 4 (8.5%) of 47 countries have data, resulting in data from Rwanda being extrapolated to 29 other countries, and from Tanzania to eight others. The Rwanda data came from another collaboration that I was involved in (Marshall 2013). Given this paucity of data, there are many gaps to be filled. Papers 1-3 provide data for three countries: Fiji, with its unusual mix of two main ethnic populations (Melanesian/Polynesian, and Indian), Bolivia (which has a high population of indigenous Amerindians), and Azerbaijan, a Turkic population on the border between Europe and Asia.

7.2 Types of diabetes in children and adolescents in less-resourced countries T1D, with its autoimmune pathogenesis and presence of diabetes autoantibodies, abrupt onset, and risk of diabetic ketoacidosis, is classically easy to distinguish from T2D, with its pathogenesis in insulin resistance with later ß-cell failure, and its slower onset, association with obesity, and resistance to ketosis. However, the distinction is not always straightforward, particularly in non- European populations, where the two conditions appear to overlap in various ways. Even in European populations, some children and youth who present with classic clinical features of T1D are autoantibody negative (Dabelea 2011, Redondo 2013), and there is some evidence that this is more common in South Asia and Africa (Balasubramanian 2003, Singh 2000, Goswami 2001, Tandon 2002, Dayal 2015, Atun 2017). Less information is available on C-peptide levels. These non-classic presentations have been variously described as ‘type 1B’, ‘idiopathic’, or ‘atypical’ forms. It has also been noted that the peak age of onset of clinically diagnosed T1D cases is later in Africa, for example this is reported in two other collaborations I have been involved with, in Rwanda (Marshall 2013) and Ghana (Ameyaw 2017). The reasons for this are not known. Possible contributing factors could include: increased heterogeneity of cases including ‘atypical’ forms, more undiagnosed deaths in younger children, and the temporal shift over recent decades where cases have increased in children <5 years of age that has occurred in European populations (presumed to be due to changing environmental triggers). As with T1D, there is also more diagnostic uncertainty regarding T2D in non-European populations in South Asia and Africa. T2D cases may not be obese or even overweight, may be ketosis-prone (Goswami 2001, Smiley 2001, Atun 2017). Aside from types 1, 2, and ‘atypical’ forms, there are other causes of diabetes in children and youth which occur around the world. There are various forms of monogenic (i.e. single gene defects) diabetes. Most of these present in the neonatal period, with a few presenting in later years (Hattersley 2019). Diabetes can also occur secondary to other causes – such as following iron overload from thalassaemia treatment. There is also the incompletely-understood entity of fibrocalculous pancreatic disease, which occurs in youth and young adults a number of tropical countries (Unnikrishnan 2015,

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Zabeen 2018). Diabetes is associated with pancreatic calcification which is visible on ultrasound or X-ray. Abdominal pain is a common feature, and the patient may be very thin. Diagnosis of the specific type of diabetes is not just of academic interest. It is important in teaching and training of local doctors and nurses, and informs genetic counselling of families as the risks of siblings being affected varies substantially between different types. Furthermore, there may be the opportunity for more personalised treatment of individual cases. If there is insulin resistance as well as ß-cell deficiency, then the patient may benefit from the addition of metformin, and some newer non-insulin hypoglycaemic agents may also be useful. Also, two forms of monogenic diabetes presenting in the neonatal period can be treated with a sulphonylurea such as glibenclamide, rather than insulin (Hattersley 2019).

7.3 Access to all components of care for young people with diabetes in less-resourced countries Even in a highly-resourced health system, T1D is a complex disorder to manage. Patients are constantly walking a tightrope, needing to avoid dangerous low- and high-blood glucose levels. Multiple insulin injections and blood glucose measurements are needed every day. Diet, exercise, and other activities must be carefully factored in. The condition is even more challenging for children and youth, with their greater variation in daily activities, increased vulnerability, growth and physical development, and changing psychosocial situations (ISPAD Guidelines 2018). Various components of care are critical for survival and then reducing or eliminating the risk of devastating long-term complications such as renal failure, blindness, amputations, and cardiovascular mortality. These include insulin, means to administer the insulin (syringes and needles or more complex devices), the ability to monitor blood glucose at home (self-monitoring of blood glucose (SMBG)), HbA1c testing, skilled health professionals who can manage diabetic ketoacidosis (DKA) and initiate and modulate insulin treatment, diabetes education, and other factors. Provision of such care is challenging in countries with very limited health budgets. Outcomes for young people with T1D in such situations are often dismal. Sididé et al. found that 10 of 20 newly-diagnosed patients in Mali died within two years (Sidibé 1999), and a further eight died within five years (Sidibé 2006). Beran et al. (2005) estimated that a child in rural Mozambique who developed T1D diabetes had a life expectancy of less than one year. When Life for a Child commenced support for children and youth in Rwanda, Tanzania, and Mali, very few young people with diabetes were known to the leading in-country centre (Atun 2017, Muze 2015, Pacaud 2016). Previous work by other groups on access to care has focused on insulin. This includes the International Diabetes Federation Insulin Task Force surveys (the first of these was published in 1994 (Deeb)), and work by the International Insulin Foundation using their Rapid Assessment Protocol for Insulin Access (RAPIA), such as their study in Mozambique and Zambia (Beran 2005). These studies demonstrated that insulin supply by public health systems was limited or absent in many countries, and that multiple challenges of allocation, logistics, distribution, and end- user costs existed even where there was some supply. More recently there has been more detailed work by the ‘Addressing the Challenges and Constraints of Insulin Sources and Supplies’

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(ACCISS) group, such as a summary article in Lancet Diabetes and Endocrinology (Beran 2016). This determined work has markedly raised awareness of this pressing issue, and had helped lead to the development of a WHO Prequalification Scheme for Insulin (WHO 2020), which aims to improve access by increasing the variety and volume of quality-assured products onto the international market. However, there has been little work published on access to the other components of care listed above (aside from additional comments in some of the papers focusing on insulin), and specifically there has been limited work on issues related to T1D in young people. With respect to costs to families of children with T1D, there is also limited information. A study from Sudan (Elrayah, 2005) found the mean annual direct cost was US$283 (23% of median income) with insulin accounting for 36% of this; and a study in Mexico (Altamirano- Bustamante 2008) found a mean annual direct cost of $1,670, which was greater than the minimum official wage of $1,460. There was virtually no self-monitoring of blood glucose (SMBG) in the Sudan group, with two tests per day in the Mexico study, wherein SMBG was responsible for 35% of the total cost. The relatively high cost of SMBG as compared to other components of care was also noted in Brazil, where the government costs of providing SMBG (a mean of 3.4 tests per day) represented 52.8% of the total costs of supplies for adults and children with T1D (Gomes, 2013). The studies included in this section are intended to help fill this gap in knowledge and thereby inform the choice and implementation of priority actions to improve this situation.

7.4 The use of clay pots and other evaporative cooling devices for insulin storage in less- resourced countries. Insulin is essential for survival in all people with T1D, and is also needed for many people with T2D. It is heat labile, and therefore all insulin products require refrigeration. Package inserts dictate that insulin must be discarded after around one month when stored at room temperature, and it should not be stored at all at higher temperatures (Grajower 2003, Grajower 2014), despite there being suggestions from studies done on animal insulin that insulin is relatively stable at modest temperature elevations (with an exponential decline which starts to sharply reduce potency once the temperature rises to the mid-30 degrees Celsius (Pingel 1972, Brange 1987, Storvick 1968)). Storage in a refrigerator is readily achievable for patients and their families in resourced countries where there are refrigerators in all homes, schools and clinics. Many countries are however not fully electrified (with an estimated 850 million globally lacking access to their homes (International Energy Outlook 2019)). Even where electricity is present in the home, in poorer areas many families do not have refrigerators. Paper 6 showed that the home refrigeration rate for families with a child with T1D was ≥67% in only one of the 19 Low-income and only six of 18 Lower-middle income countries surveyed. This can also be a problem in rural clinics (Park 2018). Patients/families generally come once every three months for their insulin supply. The families and health professionals who advise them face a difficult choice – is the insulin thrown away and more purchased with the limited resources available; or do they use it with anxiety about its potency, and potential problems with dangerous excursions of blood glucose levels.

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Compounding the challenge, insulin may be available at one clinic visit but not the next. The issue of insulin storage is a particular problem for those who live in rural areas, who often have to travel large distances at substantial cost and time to the family (Metta 2015). Families who do not have a refrigerator use different methods to try to keep the insulin cool. A neighbour or local business may have a refrigerator (Famuyiwa 1990). Where this is not possible or practical, families in many countries use traditional evaporative cooling devices to store insulin, particularly partly porous clay pots filled with water, such as that used in the DREAM Trust in Nagpur in (Pendsey 2006), a centre supported by Life for a Child. Variations on this technique had also been reported to me by other Life for a Child centres in India Tanzania, Mali, Pakistan, Haiti and other countries. The lead doctors were adamant that the technique was effective in reducing storage temperatures and increasing the time that a vial of insulin would be fully efficacious. During a visit to Khartoum in Sudan, I observed this technique being used to store insulin for a young boy. The family were squatting in a half-built house that had no power. The day I visited was very hot, and yet the water was cool to the touch. This visit prompted a review of the very limited literature on this topic, which showed inconclusive results: Shaibi et al. (1999) in Saudi Arabia found that the pots were effective in reducing temperature, however Gill et al. (2002) found minimal temperature reductions in South Africa. No study assessed the important issue of relative humidity. Therefore, the idea of a ‘Clay Pot Olympics’ developed, leading to this study (Paper 11), which tested 13 traditional cooling device designs being used in seven countries, along with a proprietary manufactured device.

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8 PUBLISHED PAPERS

8.1 Paper 1

Ogle GD, Morrison MK, Silink M, Taito RS. Incidence and prevalence of diabetes in children aged <15 years in Fiji, 2001-2012. Pediatric Diabetes 2016: 17: 222–226.

Authors: • Graham D. Ogle MBBS, FRACP, International Diabetes Federation Life for a Child Program, and Diabetes NSW. Glebe, NSW 2037, Australia Ph 61 2 9868 4446. Email [email protected] • Melinda K. Morrison APD CDE, Health & Education, Diabetes NSW, Glebe NSW 2037 Australia, Ph 61 2 9552 9968, E-mail: [email protected] • Martin Silink, AO, MD, FRACP, International Diabetes Federation Life for a Child Program, Sydney Australia, Westmead Children’s Hospital, Sydney, Australia, University of Sydney, Australia. Ph 61 2 9845 3172, Email: [email protected] • Rigamoto S. Taito MBBS, DCH, MMed Paeds, Department of Paediatrics, Lautoka Hospital, Lautoka, Fiji. Ph 679 6660399, Email: [email protected] Corresponding author: Graham D. Ogle MBBS, FRACP, International Diabetes Federation Life for a Child Program, and Diabetes NSW. Glebe, NSW 2037, Australia Word count: 2,258

Abstract Objective: Determine the incidence and prevalence of diabetes in children <15 years in Fiji. Methods: Data on all new cases from 2001-12 was collected from the three paediatric diabetes services through the International Diabetes Federation Life for a Child Program. There was no formal secondary ascertainment source, however the medical community is small and all known cases are believed to be included. Results: 42 children aged <15 years were diagnosed from 2001-2012. 28 were type 1 (66.7%), 13 type 2 (31.0%), and one (2.4%) had neonatal diabetes (INS gene mutation). For type 1, the mean±SD age of diagnosis was 10.2±2.9 years, with similar proportions of males and females. Four (14.3%) were native Fijians and 24 (86.7%) were of Indo-Fijian descent (p<0.001). The mean annual incidence of type 1 in children <15 years was 0.93/100,000 and prevalence in 2012 was 5.9/100,000. There was no evidence of a rise in incidence, but low numbers would preclude recognition of a small increased rate. For the 13 cases of type 2 diabetes, the mean SD age of diagnosis was 12.2±2.7years, 85% were female (p<0.01), and 85% were of Indo-Fijian descent (p=0.001). The mean annual incidence of type 2 was 0.43/100,000 and 2012 prevalence was 2.4/100,000. No child with diabetes aged <15 years died during the 12 year period. Conclusions: The incidence of type 1 diabetes in Fiji is very low. Furthermore, its occurrence is markedly more frequent in Indo-Fijians than in native Fijians. Type 2 and neonatal diabetes also occur. Keywords: diabetes, incidence, prevalence, Fiji, India

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Introduction Fiji is a small island nation located in the South Pacific. In 2007, Fiji had an estimated population of 837,271, comprised predominately of native Fijians, Indo-Fijians originating from the Indian sub-continent [1]. Epidemiological studies of diabetes were first undertaken in Fiji in 1964, where it was reported that juvenile diabetes was extremely rare[2]. At this time there were only six known cases of diabetes in those aged < 20 years, with no cases reported in ethnic Fijians [2]. Since then, there have been no published studies on diabetes in young people in Fiji, with International Diabetes Federation (IDF) Atlas [3] estimates extrapolated from studies in Papua New Guinea (PNG) [4]. In 2001, the IDF Life for a Child Program (LFAC) commenced supporting the country’s three paediatric centres - Lautoka, Suva and Labasa. The aim of this paper is to report the incidence and prevalence of diabetes in children <15 years of age in Fiji from 2001- 2012.

Methods Data on all new cases of paediatric diabetes was collected from the three paediatric diabetes services in Fiji through the LFAC Program. As per LFAC protocol, Annual Clinical Data Sheets were completed for children enrolled in the program from 2001 to 2012. These Data Sheets collate the demographic, clinical and diabetes management information that is regularly obtained as part of standard clinical practice. The type of diabetes was diagnosed on the basis of history and clinical features as C-peptide and antibody assays were not available in Fiji during this period. One child presented before six months of age and so genetic testing was conducted by the Molecular Genetics Laboratory at the University of Exeter Medical School, United Kingdom.

Ascertainment Cases of diabetes were ascertained from annual data sheets provided by the treating medical officers at each of the three paediatric diabetes services. All cases of known diabetes were confirmed to be enrolled in the program and attending one of these centres. Due to the absence of a formal diabetes register in Fiji, formal secondary ascertainment of data was not possible. However the medical community is small and enquiries did not reveal any cases outside these three hospitals.

Incidence & Prevalence Annual incidence of type 1 and type 2 diabetes was calculated per 100,000 children <15 years of age, from 2001 to 2012 using childhood population estimates from Fijian census data [1]. Data from the 1996 census indicated that there were 274,377 children and adolescents under the age of 15 years in Fiji, and 243,121 of the same age in the 2007 census. The number of children in Fiji for each year of data collection was interpolated using the mean annual change in the population of children aged <15 years for an intercensal period of eleven years from 1996- 2007. Estimated childhood population figures for 2008 and 2012 were interpolated from the 2007 census to the CIA World Fact Book 2013 population figures of 254,312 children aged 0-14

17 years [5]. Prevalence was reported as total number of prevalent cases aged <15 years in 2001 and 2012 and number of cases per 100,000 children <15 years of age, using the same method as described above. Comparisons between observed and expected rates in ethnic groups were completed using Pearson’s chi square goodness of fit test based on 2007 census data in which 56.8% of the population was native Fijian, 37.5% Indo-Fijian and 5.7% non-Indian non-Native Fijians.

Results From 2001 to 2012 inclusive there were 42 cases of diabetes diagnosed in children under the age of 15 years. There were no reported deaths in children aged <15 years with diabetes in Fiji during this time. Diagnoses were more predominant in Lautoka (45%), followed by Suva (43%) and Labasa (12%). Overall, there were 28 cases of type 1 (66.7%), 13 cases of type 2 (31.0%), and one case of neonatal diabetes (2.4%). The majority of cases of diabetes were diagnosed in Indo-Fijians (83.3% - 35 cases) with 14.3% (6 cases) in native Fijians and 2.4% (1 case) in Fijians of European descent. The prevalence of all types combined was 7.3/100,000 children <15 years in 2001 and 8.7/100,000 in 2012.

Type 1 For the 28 cases of type 1 diabetes, the mean SD age of diagnosis was 10.2 ± 2.9 years (range 3.7-13.5). Two (7.1%) were aged 0-4 years, nine (35.7%) aged 5-9, and 17 (57.1%) 10-14. Figure 1 shows a histogram of diagnoses according to age. Fifteen (53.6%) were boys, and 13 (46.4%) were girls. Four (14.3%) were native Fijians and 24 (85.7%) were of Indo-Fijian descent (p<0.001). Table 1 shows the annual incidence of type 1 diabetes (expressed as number of cases per 100,000 children <15 years) for the years 2001-2012. The mean annual incidence of type 1 diabetes in children during this period was 0.93 per 100,000. The prevalence of type 1 was 6.5 per 100,000 in 2001 and 5.9 per 100,000 in 2012. For the two ethnic groups, the mean incidence for native Fijians was 0.23 per 100,000 and for Indo-Fijians 2.14 per 100,000 and prevalence in 2012 was 1.4 per 100,000 and 13.6 per 100,000 respectively. The mean BMI Z-score of the children with type one was -0.05 (data available on 25 subjects).

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Figure 1 – Age at presentation for diagnosis of type 1 diabetes in children in Fiji

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Table 1: Annual incidence (per 100,000) of diabetes in children aged <15 years in Fiji Year of Type 1 diabetes Type 2 diabetes All types of diabetes diagnosis N Incidence N Incidence N Incidence per 100,000 per 100,000 per 100,000 2001 2 0.77 1 0.38 3 1.15

2002 2 0.78 3 1.17 5 1.94

2003 1 0.39 1 0.39 3* 1.18

2004 1 0.40 1 0.40 2 0.79

2005 4 1.61 2 0.80 6 2.41

2006 2 0.81 0 0.00 2 0.81

2007 4 1.65 1 0.41 5 2.06

2008 2 0.82 0 0.00 2 0.82

2009 2 0.81 1 0.40 3 1.21

2010 4 1.60 0 0.00 4 1.60

2011 3 1.19 0 0.00 3 1.19

2012 1 0.39 3 1.18 4 1.57

2001-2012 28 0.93 13 0.43 42 1.40

* Includes one case of neonatal diabetes

Type 2 For the 13 cases of type 2 diabetes, the mean SD age of diagnosis was 12.2 ±2.7years (range 6.5- 14.8). Three (23%) were aged 5-9 years, and 10 (77%) 10-14 years. Two (15%) were boys, and 11 (85%) were girls (p<0.01). Eleven cases (85%) were of Indo-Fijian descent, one (7.7%) Fijian of European descent and one reported case in a native Fijian child (7.7%) (p=0.001 for Indo- Fijians v Native Fijians). Table 1 shows the annual incidence of type 2 diabetes (expressed as number of cases per 100,000 children <15 years) for the years 2001-9. The mean annual incidence of type 2 diabetes in children during this period was 0.43 per 100,000. The prevalence was 0.38/100,000 in 2001 and 2.4/100,100 in 2012. Four of the children with type 2 commenced insulin at diagnosis, four started on metformin, and five were initially managed with diet and exercise. The mean BMI Z-score of the 13 children with type two was 1.49.

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Neonatal Diabetes One child was diagnosed aged five months (a boy). Genetic analysis revealed that he had a heterozygous INS gene mutation (p.C96S) INS mutation. This child had an older brother with diabetes diagnosed at 6 weeks of age, but before 2001. This youth also has the INS mutation. Their father (unaffected by diabetes) was mosaic for this mutation with an estimated mosiacism level in his leukocyte DNA of 29%.

Discussion The global incidence of type 1 diabetes in children and adolescents varies widely, with a more than 100-fold difference in annual incidence rates reported between countries [4,6,7,8]. Asian populations generally have lower rates than European populations [6,7,8]. Various genetic and environmental factors have been implicated in these differences [7,8], but much still remains unclear. The mean annual incidence of type 1 diabetes in children in Fiji during 2001-2012 of 0.93/100,000 children <15 years is very low. The annual incidence in 2006 in Australia was 23.4/100,000, and 17.9/100,000 in New Zealand in 1999-2000 [9,10]. The only other published data from the South Pacific is from PNG, which has a very low annual incidence of 0.08/100,000 [4]. The similar sex ratio, and the age pattern whereby the onset was least common in the youngest children (0-5 years) and most common in older children (10-14 years), are consistent with patterns in other countries [7]. There was no evidence of a rise in incidence (as is being seen in many other countries [6,8,9], but the low numbers would preclude recognition of any increase at the rate being seen in these other countries (around 3%). The study has several limitations that may have affected the accuracy of incidence and prevalence estimates. The lack of C-peptide and antibody assays may have led to an over- or under-estimation of the number of cases of each type of diabetes. However, the small number of young people with diagnosed diabetes and frequent follow-up and monitoring of cases through the LFAC program should have helped reduced any misclassification bias. While secondary ascertainment was not possible, the relatively small population and the structure of and inter-relationship within the Fijian health care system make it very unlikely that there were any other diagnosed cases during this period. The differences in incidence and prevalence depending on ethnicity were striking, with 87% of cases of type 1 diabetes in Indo-Fijians despite this group being only 37% of the population. This is consistent with Cassidy’s study in 1964-5 which found that there were no native Fijians represented in the six cases of known diabetes less than 20 years old [2]. Native Fijians are a mixture of Melanesian and Polynesian extraction. The almost wholly-Melanesian population of PNG has an extraordinarily low incidence of type 1 diabetes in children, although it is possible that some children may be undiagnosed in that country [4]. In Fiji, it is also possible that the occasional child dies of diabetic ketoacidosis that is misdiagnosed as another condition (such as pneumonia or gastroenteritis). However, awareness of the symptoms of diabetes is relatively high amongst health professionals in Fiji, and there are less challenges from geography than in PNG, and so children can be more easily referred to a secondary or tertiary level facility.

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It is unclear why there should be such a difference between the two ethnic groups. With respect to environment, many factors would be expected to be similar amongst the two groups. Average incomes are comparable, with ethnic Fijians being slightly higher on average [11]. Dietary habits are on the whole different, but have substantial overlap. Differing genetic predisposition likely plays a substantial role. In the literature, marked differences have been noted between the island populations of Sardinia and Crete compared to their respective neighbouring mainland [6]. The average annual incidence of type 1 diabetes in Indo-Fijian children is lower than the to the limited published incidence data from India [12,13]. Rates in another Polynesian population – New Zealand Māoris are 4.5 times less than in European New Zealand children [10]. The cases of type 2 diabetes are the first report of this condition in children in Fiji. Indeed, the first few cases of type 2 were initially diagnosed and treated as type 1 and then later re-categorised after review by LFAC. There were more cases in girls than boys, as per other published reports [14,15,16]. Type 2 diabetes was also more common in Indo-Fijian youth. Indians are known to have high rates of type 2 in adults, and type 2 is not infrequently seen in children [17,18], although there are high rates of type 2 in adults in other parts of Melanesia and Polynesia [19,20]. In the 2002 STEP national study, 21.2% of Indo-Fijians aged 25-64 had diabetes compared to 11.5% of Native Fijians [21]. Brian et al [22] also found that rates in females were higher than in males in both ethnic groups. The possibility of undiagnosed cases is of major concern as these young people may already be developing microvascular complications [23]. As westernisation continues in the Pacific, the numbers of children at risk of type 2 diabetes will rise. In a prospective study in New South Wales, Australia 12% of cases of type 2 in children were of Māori/Polynesian/Melanesian descent despite this group being a small proportion of the overall population [24]. The heterozygous INS mutation (p.C96S) has been previously reported [25,26]. This form of monogenic diabetes is not responsive to oral therapy and requires insulin as with type 1 diabetes. These two cases are, to our knowledge, the first reports of monogenic diabetes in a Melanesian or Polynesian population. There is limited information on mortality in children with diabetes in developing countries; however we are aware of many deaths in various countries where there is limited access to insulin and clinical care. Beran et al. estimated an average life expectancy after diagnosis of 11.2 years in Zambia and 3.5 years in Mozambique [27]. It is encouraging that no children aged <15 years with diabetes died in Fiji during this 12 year period. The Government of Fiji provide insulin and medical care free to children, and also provide some support with blood glucose monitoring, which has increased over the study period. IDF Life for a Child Program supported extended self-monitoring of blood glucose until the government supply was adequate, and has also provided health professional training, technical support, patient education materials, and assistance with diabetes camps. In conclusion, type 1 diabetes is uncommon in Fiji. It is markedly more frequent in Indo-Fijians than in native Fijians. Type 2 diabetes is now also being diagnosed in children in this country, and neonatal diabetes also occurs. Further studies on the epidemiology of type 1 and type 2 diabetes in children in the South Pacific are warranted.

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Acknowledgements The authors wish to acknowledge the medical personnel involved in the IDF LFAC Program in Fiji since 2001: Dr Shabnam Prakash (2001 - r2002), Dr Laila Sauduadua (2001 – 2012), Dr Isaiah Immanuel (2006 – 2010), Dr Aida Tamargo (2001 – 2002), Dr Myla Mapago (2002 – 2005), Dr Rosa Sa’aga (2001 – 2002), Dr Miriam Tukana (2010 - 2012 ). We thank Drs Joseph Kado and Asena Tuiketai for facilitating the genetic testing, Angela Middlehurst for assistance with collecting and compiling data, and Johlene Morrison for administrative assistance. We also thank Dr. Sian Ellard and the team at the Molecular Genetics Laboratory at the University of Exeter (United Kingdom) for conducting the genetic assays for neonatal diabetes, and Rachel Miller (University of Pittsburgh) for statistical support.

References 1. Census 2007 Results, Fiji Islands Bureau of Statistics, 2008. 2. Cassidy, J.T, Diabetes in Fiji. NZ Medical Journal, 1967:66:167-172. 3. Diabetes Atlas. Third Edition. Brussels: International Diabetes Federation, 2006. 4. Ogle GD, Lesley, J, Sine P, McMaster P, Type 1 diabetes mellitus in children in Papua New Guinea. PNG Med J 2001; 44:96-100. 5. Central Intelligence Agency. (2013) Fiji. In The world factbook. Retrieved from https://www.cia.gov/library/publications/the-world-factbook/geos/fj.html 6. The DIAMOND Project Group. Incidence and trends of childhood Type 1 diabetes worldwide 1990-1999. Diabet Med 2006;23:857-866. 7. Soltesz G, Patterson CC, Dahlquist G on behalf of EURODIAB Group. Worldwide childhood type 1 diabetes incidence – what can we learn from epidemiology? Pediatr Diabetes 2007;8 (Suppl 6):6-14 8. Craig ME, Jeffries C, Dabelea D et al. Definition, epidemiology and classification of diabetes in children and adolescents. Pediatr Diabetes 2014;15(Suppl. 20):4-17. 9. Australian Institute of Health and Welfare 2010. Incidence of Type 1 diabetes in Australian children 2000–2008. Diabetes series no. 13. Cat. no. CVD 51. Canberra: AIHW. 10. Campbell-Stokes PL, Taylor BJ, New Zealand Children’s Diabetes Working Group. Prospective incidence study of diabetes mellitus in New Zealand children aged 0 to 14 years. Diabetologia 2005;48:643-648. 11. Narsey, W. Report on the 2002-3 household income and expenditure survey. Suva; Fiji Bureau of Statistics, 2006 (cited 2011 July 26). Available from: www.pacifichealthvoices.org/files/Fiji%20NCD%20steps%20survey%202002.pdf 12. Ramachandran A, Snehalatha C, Krishnaswamy CV. Incidence of IDDM in children in urban population in Southern India. Diab Res Clinical Pract 1996;34:79-82 13. Kumar P, Krishna P, Reddy SC, Gurappa M, Aravind SR, Munichoodappa C. Incidence of type 1 diabetes mellitus and associated complications among children and young adults: Results from Diabetes Registry 1995-2008. J Indian Med Assoc 2008;106:708-711 14. Pinhas-Hamiel O, Zeitler P. Clinical presentation and treatment of type 2 diabetes in children. Pediatr Diabetes 2007;4(Suppl 9)16-27 15. Gill-Carey O, Hattersley AT. Genetics and type 2 diabetes in youth. Pediatr Diabetes 2007;8(Suppl 9):42-47.

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16. Zeitler P, Fu J, Tandon N et al. Type 2 diabetes in the child and adolescent. Pediatr Diabetes 2014;15(Suppl. 20) 26-46. 17. Ramachandran, A, Snehalatha,C, Satyavani, K, Sivasankari, S, Vijay, V. Type 2 diabetes in Asian-Indian urban children. Diabetes Care 2003; 26(4):1022-1025. 18. Mohan V, Jaydip R, Deepa R. Type 2 diabetes in Asian Indian youth. Pediatr Diabetes 2007;8(Suppl 9) 28-34. 19. Ogle GD. Type 2 diabetes mellitus in Papua New Guinea – an historical perspective. PNG Med J 2001;44:81-87. 20. Colagiuri S, Colagiuri R, Na’ati S, Muimuiheata S, Hussain Z, Palu T. The prevalence of diabetes in the kingdom of Tonga. Diabetes Care 2002; 25(8): 1378-1383. 21. Cornelius M, DeCourten M, Pryor J, Saketa S, Waqanivalu TK, Laqeretabua A, Chung E. Fiji non-communicable diseases (NCD) STEPS Survey 2002, Fiji Ministry of Health, 2002. 22. Brian G, Ramke J, Maher L, Page A, Szetu J. The prevalence of diabetes among adults aged 40 years and over in Fiji. N Z Med J. 2010;123:68-75. 23. Dean HJ, Sellers EAC. Comorbidities and microvascular complications of type 2 diabetes in children and adolescents. Pediatr Diabetes 2007:8(suppl 9):35-41. 24. Craig M, Femia G, Broyda V, Lloyd M, Howard NJ. Type 2 diabetes in Indigenous and non- Indigenous children and adolescents in New South Wales. Med J Aust 2007;186:497-499. 25. Edghill EL, Flanagan SE, Patch A-M et al. Insulin mutation screening in 1,044 patients with diabetes. Diabetes 2007;57:1034-1042. 26. Rubio-Cabezas O, Hattersley AT, Njølstad PR et al. The diagnosis and management of monogenic diabetes in children and adolescents. Pediatr Diabetes 2014;15(Suppl. 20):47-64. 27. Beran D, Yudkin JS, de Courten M. Access to care for patients in insulin-requiring diabetes in developing countries: Case studies of Mozambique and Zambia. Diabetes Care 2005;28:2136-2140.

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8.2 Paper 2

Duarte Gómez E, Gregory GA, Castrati Nostas M, Middlehurst AC, Jenkins AJ, Ogle GD. Incidence and mortality rates and clinical characteristics of type 1 diabetes among children and young adults in Cochabamba, Bolivia. Journal of Diabetes Research 2017; 8454757.

Authors and Institutions: 1 Elizabeth Duarte Gómez email: [email protected]. Tel : 591-4-4416888. 2,3 Gabriel Andrew Gregory email: [email protected] 1 Miriam Castrati Nostas email: [email protected] 2,4 Angela Christine Middlehurst email: [email protected] 3 Alicia Josephine Jenkins email: [email protected] 2,3,4 Graham David Ogle email: [email protected]

1 Centro Vivir con Diabetes, Av. Simón López # 375, Cochabamba, Bolivia. 2 International Diabetes Federation Life for a Child Program, Glebe, NSW 2037, Australia 3 NHMRC Clinical Trials Centre, University of Sydney, NSW 2006, Australia 4 Diabetes NSW, Glebe, NSW 2037, Australia

Corresponding author – Graham Ogle, [email protected]. Tel +61 400 683 574.

Author’s contributions ED collected the data, and contributed to the manuscript; GG analysed the data and wrote the manuscript; MC collected the data and contributed to the manuscript; AM assisted in data analysis and contributed to the manuscript; AJ helped with interpretation of the data and contributed to the manuscript; GO designed the study and co-wrote the manuscript.

Supportive Foundations: This work was supported by the Leona M and Harry B Helmsley Charitable Trust. GG was partly funded by a University of Sydney Summer Research Scholarship. AJJ is funded by a NHMRC (Australia) Practitioner Fellowship and a Sydney Medical School Foundation Fellowship.

Institutional review board statement: The study was reviewed and approved by the Board of Centro Vivir con Diabetes.

Conflict of interest statement: None of the authors have any conflicts of interest in regard to this study.

Data sharing statement: Not relevant

Correspondence to: Dr. Graham Ogle, [email protected]

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Keywords: children, diabetes, developing countries, Bolivia, mortality

Abstract Objectives: Determine incidence, mortality rate, and clinical status of youth with diabetes at the Centro Vivir con Diabetes (CVcD), Cochabamba, Bolivia, with support from International Diabetes Federation Life for a Child Program. Methods. Incidence/mortality data analysis of all cases (<25 year (y)) diagnosed Jan 2005-Feb 2017, and cross-sectional data (Dec 2015). Results: Over 12.2 years, 144 cases were diagnosed, all type 1 (T1D); 43.1% male. Diagnosis age was 0.3-22.2 year (y), peak onset was 11-12y. 11.1% were <5y, 29.2% 5-<10y, 43.1% 10-<15y, 13.2% 15-<20y, 3.5% 20-<25 y. The youngest is being investigated for monogenic diabetes. Measured incidence in Cercado Province (Cochabamba Department) was 2.2/100,000 <15y/y, with ≈80% ascertainment, giving total incidence of 2.7/100,000 <15y/y. Two had died. Crude mortality rate was 2.3/1,000 patient years. Clinical status data on 141 cases aged <35 y being seen in late 2015 were analysed. Mean/median HbA1c were 8.5/8.2% (69/62 mmol/mol) and were higher in adolescents. Three were on renal replacement therapy, four others had substantial renal impairment. Elevated BMI, fasting triglycerides, and total cholesterol were common: 19.1%, 18.3%, and 39.1% respectively. Conclusions: Bolivia has low T1D incidence. Reasonable glycaemic control is being achieved despite limited resources, however some youth have serious complications and adverse cardiovascular risk factor profiles. Further attention is needed to prevent, screen for, and treat chronic complications.

Introduction For any nation, understanding the epidemiology and clinical status of young people with diabetes is essential for training of health professionals, and also for conducting advocacy with the respective government to plan and improve the appropriate clinical services. Very little published material is available on diabetes in youth in Bolivia. The International Diabetes Federation (IDF) Atlas estimates of children <15 years with type 1 diabetes in Bolivia[1] are extrapolated from data from Peru that is over two decades old [2,3], a time during which the incidence of type 1 diabetes has been increasing at 2-3% or more per annum in many countries.[1] In 2005, the IDF Life for a Child Program (LFAC)[4], with the assistance of Rotary International, commenced support for the Centro Vivir con Diabetes (CVcD), a multidisciplinary clinic in Cochabamba. Satellite networks were established in five other cities. LFAC commenced professional mentoring and provision of insulin (initially with support of Insulin for Life Australia.[5] Later blood glucose meters and test strips (three tests/day), HbA1c testing, and educational materials were provided. This study presents epidemiological data on all young people with diabetes known to CVcD from Jan. 2005 to early 2017, the clinical features of the cohort receiving care at the end of 2015 and documents the initial impact of the LFAC program.

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Materials and Methods The study was approved by the Board of Centro Vivir con Diabetes. Epidemiology data Data (age, gender and diabetes type) were compiled on all people diagnosed with diabetes at age <25 years (y) and seen by CVcD and its five satellite clinics from Jan 2005 to Feb 2017. Diabetes was diagnosed according to standard World Health Organization (WHO) criteria [6], and diabetes type determined by the local investigators based on clinical features. It is not possible to determine the exact national incidence as other diabetes care providers exist in Bolivia, and no secondary ascertainment sources are available. However, in Cochabamba Province – comprising Cochabamba city and its immediate environs - where 63 (43.8%) of cases were living at diagnosis, CVcD is well-known and the ascertainment rate is estimated at 80%. A minimum incidence for Cercado Province was calculated according to census data[7], with population interpolated or extrapolated according to the annual growth rate of 1.6%.[8] The crude mortality rate was calculated as the total number of deaths in the cohort of 144 subjects divided by the total number of years from diagnosis until last follow-up (Feb. 2017) or, if they had died, date of death. Results are expressed as mortality per 1,000 patient years.

Clinical status Clinical information was collated on all 141 subjects being followed from September to December 2015, who were aged <25y at diabetes diagnosis and at time of this assessment were ≤ 35 y. This 141 included some cases diagnosed before Jan 2005, and excluded some cases included in the incidence study who were now being seen by other centres. The data were collected via LFAC Annual Clinical Data Sheets. Data included sex, date of birth, diabetes diagnosis date, details of diabetes treatment regimen, and physical and biochemistry measures. Also, social parameters as to whether diabetes was limiting school attendance; if they were in the age appropriate grade; and how well overall the young person was, in their doctor’s opinion psychologically coping with their diabetes (rated as good, some problems, or poorly); were also recorded. Body weight and height were measured by electronic scales and stadiometer respectively with subjects wearing light-weight clothing and without shoes. Body Mass Index (BMI) was then calculated. BMI SD scores were calculated using the WHO standards for <5 years [9], and for >5 years and <19 years.[10] Blood pressure SD score was calculated from published data from the Unites States.[11] The presence of cataracts, retinopathy and peripheral neuropathy was recorded. However, the methodology was not prescribed, and therefore could have varied across centres and physicians.

Biochemistry: Glycosylated haemoglobin (HbA1c), serum creatinine, total cholesterol, triglycerides and HDL- cholesterol were measured in local biochemistry laboratories, with the exception of HbA1c at Cochabamba where it was measured with a Siemens DCA Vantage machine (Erlangen, Germany). Lipid tests were done on fasting samples. LDL-cholesterol was calculated using the Friedewald equation, hence is only available on the subset of patients who had HDL-cholesterol levels.[12]

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Estimated Glomerular Filtration Rate (eGFR) was calculated for those ≥ 14 y by the CKD- EPI (Chronic Kidney Disease Epidemiology Collaboration) formula[13], adjusted for individual surface area.

Initial Impact of Life for a Child Program was measured by assessing all HbA1c levels of all subjects having data at baseline (program commencement in 2004) and then at either six- or 12- months follow-up.

Statistics Data and descriptive statistics were managed in Excel and analysed in R 3.3.1 (R Core Team, Vienna, Austria) with R Studio integrated development environment (R Studio Team, Boston, USA).

Results 1. Epidemiological data 1.1 Sex distribution and age of onset Of the 144 subjects diagnosed at age <25 y between Jan 2005 and Feb 2017, 62 (43.1%) were males. Age of onset ranged from 0.3-22.2 y, with a peak at 11 years (see Figure 1 histogram). Sixteen subjects (11.1%) were diagnosed at age 0-4 y, 42 (29.2%) were diagnosed aged 5-9 y, 62 (43.1%) were diagnosed aged 10-14 y, 19 (13.2%) were diagnosed aged 15-19 y, and 5 (3.5%) were diagnosed aged 20-24 y. Genetic studies are being arranged for the child diagnosed at 3-months to check for a monogenic form of diabetes. This child has no other medical problems.

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Figure 1: Age at diagnosis of type 1 diabetes in Bolivia, 2005-2017.

1.2 Minimum incidence Sixty-three cases of diabetes (diagnosed <25 years of age) occurred in the Cercado Province of Cochabamba Department in the 12.2 y study period from Jan 2005–Feb 2017. Forty-nine were <15 y at diagnosis and 14 were 15-24 y. This is a measured incidence of 2.2 per 100,000 children <15 y/y. Ascertainment is estimated as 80%, resulting in an estimated total incidence of 2.7 per 100,000 <15y/y.

1.3 Mortality rate Of the 144 subjects followed up for 0.1-12.2 y (mean ± SD 5.9 ± 3.4y) two had died; a male aged 22.8 y from gastric ulcer haemorrhage and a female aged 13.4 y from ketoacidosis (who had been abandoned by her family). The crude mortality rate was 2.3 / 1,000 patient years.

2. Clinical status 2.1 Demographics One hundred and forty-one T1D subjects diagnosed <25 years of age and ≤ 35 y were being followed by CvCD at the end of 2015. Sixty-four (45%) patients were male. Sixty (43%) were from Cochabamba Department, 31 (22%) Santa Cruz, 27 (19%) La Paz, 12 (8.5%) Sucre, 6 (4.3%) Tarija, and 5 (3.5%) were from Potosi. One child also had cerebral palsy, one had Down’s syndrome, and one child also had epilepsy. Age at diagnosis and diabetes duration are shown in Table 1.

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Table 1 – Clinical and biochemical characteristics Parameter n Mean (SD) Range Age at diagnosis (years) 141 9.9 (4.4) 0.3-22.2 Diabetes duration (years) 141 8.1 (5.7) 0.1-26.9 BMI SD Score 137 0.9 (1.1) -2.2-3.7 Systolic SD Score 21 0.7 (0.8) -1.4–2.0 Diastolic SD Score 21 1.1 (0.7) -0.1–2.6 HbA1c (%)* 135 8.5 (1.9) % 5.4–14.0% HbA1c (mmol/mol)* 135 69 (21) mmol/mol 36–130 mmol/mol Serum creatinine (mg/dl) 130 0.92 (0.69) 0.5–6.2 Total Cholesterol (mg/dl) 122 167 (43.2) 81-334 Triglycerides (mg/dl) 121 112 (63) 42-497 HDL Cholesterol (mg/dl) 27 43 (14.2) 7.9-59 LDL Cholesterol (mg/dl, 27 124 (38) 43-191 calculated) Non-HDL Cholesterol (mg/dl, 27 149 (44) 58-216 calculated) * HbA1c not included on six subjects assessed within six months of diagnosis

2.3 Diabetes care Ninety-four subjects (67%) were adjusting their insulin dose (data available on 141), with the remainder giving a fixed insulin dose set in agreement with their treating clinicians. Regarding insulin types (n = 138), 99 (72%) were on short and long-acting human insulin only. Twenty-five (18%) were using analogue insulin, of which nine (7%) were using analogue only. Thirteen (9%) were on pre-mixed insulin and one patient was receiving long-acting human insulin only. For the number of insulin injections per day (n = 122), 18 subjects (158%) were taking two injections per day, 70 (57%) three, 24 (20%) four, and the remaining 10 (8%) were taking five injections daily. Insulin usage ranged 0.35 - 1.76 Units/kg/day, mean ± SD 0.99 ± 0.29 (n = 136). The frequency of self-blood glucose tests per week (n = 139), was 14 - 28 (mean ± SD 21.3 ± 1.4). The frequency of clinic visits in the last year (n = 131) was 1 - 8 (mean ± SD 3.5 ± 1.3).

2.4 Social parameters School / college attendance was regular in 93 (96%) of the 97 patients for whom this information was available, and the year of schooling was age-appropriate in 94%. Out of 105 patients for whom a response was recorded on the question of how well they thought their patients were coping with their diabetes, 62 (59%) of responses were ‘good’, 38 (37%) were ‘some problems’, and four (4%) were ‘poorly’.

2.5 Physical measurements Height and weight information were available for 137 patients, and 81 of these were under 19 years, permitting BMI SD Score calculation (shown in Table 1).

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Blood pressure was measured on 21 subjects < 20 years, with systolic and diastolic SD scores shown in Table 1. Both systolic and diastolic mean SD score were above zero (p<0.001 for both, by one-sided t test). None of the patients for whom SD scores were available were noted to have hypertension (as defined by local clinical standards), or be on antihypertensive medications.

2.6 HbA1c HbA1c was measured in the 135 subjects with duration of diabetes >6 months. Mean and median HbA1c were 8.5% (69 mmol/mol) and 8.2 % (66 mmol/mol) respectively (see also Table 1). Forty-four subjects (33%) had HbA1c levels in the recommended target range of <7.5% (58 mmol/mol), 35 (25%) 7.5% -8.49% (58-69 mmol/mol), 48 (36%) 8.5%-12% (69-108 mmol/mol) and the remaining eight subjects (5.8%) > 12% (108 mmol/mol). Twenty-six percent of those < 15 y and 30% of those 15-24 y had target HbA1c <7.5% (58 mmol/mol). A series of one-way ANOVAs on log-transformed HbA1c levels was performed, finding trends towards relationships between HbA1c levels, the number of insulin injections per day (p=0.07), and the use of analogue insulin (p=0.06), but not for gender (p=0.38). A pattern of increased HbA1c levels and variance during adolescence was observed from a plot of HbA1c by age (Figure 2). For those aged 0-13 y, the HbA1c mean ± SD was 7.9% (63 mmol/mol) ± 1.3% (14 mmol/mol), for 13-20 y 9.4% (78 mmol/mol) ± 2.0%, and > 20 y, 7.9% (63 mmol/mol) ± 1.7% (18 mmol/mol). This indicates a significant difference in HbA1c levels between age groups (p=0.0002 by one-way ANOVA on log-transformed values). However, Levene's test for heterogeneity of variance was not statistically significant (p=0.24).

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Figure 2: Relationship of age to HbA1c

7.5% 58 mmol/mol

Mean/median HbA1c levels by diabetes clinic site were 9.0%/8.4% (75/68 mmol/mol) in Cochabamba, 7.9%/7.6% (63/60 mmol/mol) in La Paz, 8.0%/7.4% (64/57 mmol/mol) in Potosi, 8.5%/8.4% (69/68 mmol/mol) in Santa Cruz, 8.5%/8.3% (69/67 mmol/mol) in Sucre and 7.1%/6.8% (54/51 mmol/mol) in Tarija, with no statistical difference between clinics on ANOVA.

2.7 Lipids Lipid levels are shown in Table 1. No subjects were on lipid-lowering agents. For Total Cholesterol, 97 patients (80%) were < 200 mg/dl (5.2 mmol/l), 16 patients (13%) 200-239 mg/dl (5.2-6.2 mmol/L), and nine (7.3%) (≥ 240 mg/d1) (≥ 6.2 mmol/L). Total cholesterol levels were not correlated with concurrent HbA1c levels (p = 0.14 by Pearson’s correlation). Triglyceride levels (n=121) were < 1.7 mmol/L (150 mg/dL) in 99 patients (82%), 1.7-2.2 mmol/L (150-199 mg/dL) for 11 (9%) patients, and 2.3-5.6 mmol/L (200-499 mg/dL) for 11 (9%) (all subjects were < 4.5 mmol/l (450 mg/dl). Log-transformed triglyceride levels correlated with concurrent HbA1c levels (p = 0.03 by Pearson’s correlation). HDL-cholesterol was measured in 27 patients from the Department of La Paz – see Table 1. None of these patients were on renal replacement therapy. Fifteen patients (56%) had HDL < 1.0 mmol/L (40 mg/dL) for men or 1.3 mmol/L (50 mg/dL) for women. There were no significant correlations between HDL-cholesterol and either HbA1c or log-transformed triglyceride levels.

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Seven patients (26%) had calculated LDL-cholesterol levels < 100 mg/dl (<2.6 mmol/l), 10 patients (37%) 100-129 mg/dl (2.6-3.3 mmol/l), and 10 patients (37%) ≥ 130 mg/dl (3.3 mmol/l). Table 2 shows the percentage of subjects meeting target levels for cardiovascular risk factors (BMI, triglycerides, total cholesterol, and HbA1c), for the 115 subjects that had values for all four measurements.

Table 2 – Risk Factors for Cardiovascular Disease Risk Factor Definition n % High BMI For <19 years, SD Score 22 19.1 ≥ 2.0; if ≥ 19 years BMI of ≥ 25 Elevated fasting ≥ 150 mg/dl (≥ 1.7 21 18.3 triglycerides mmol/l) Elevated fasting total ≥ 175 mg/dl (≥ 4.5 45 39.1 cholesterol mmol/l) HbA1c above target ≥ 7.5 % (58 mmol/mol) 74 64.3 range One risk factor ------44 38.3 Two risk factors ------34 29.6 Three risk factors ------14 12.2 Four risk factors ------2 1.7 (n=115)

2.8 Renal function Serum creatinine values are shown in Table 1. Five patients (4%) had serum creatinine levels above the recommended level of 1.3 mg/dL (115 μmol/L) for males or 1.1 mg/dl (97 μmol/L) for females. eGFR for the 115 subjects ≥ 14 y ranged from 10.4 - 178.9 mL/min/1.73m2 (mean ± SD 104.9 ± 31.0 mL/min/1.73m2). Three patients on renal replacement therapy (see below) were excluded from this analysis. Two subjects were receiving haemodialysis (age 28.5 and 28.8 y) (duration of diabetes to start of haemodialysis 16.5 and 1.25 y), one had received a renal transplant after 0.3 y on haemodialysis (age 30.4 y, duration of diabetes to time of haemodialysis 17.3 y) and one other was noted as having chronic renal failure (24.4.y, duration 20.5 y, eGFR 12.8 ml/min/1.73m2). Three other subjects had eGFR <50 ml/min/1.73m2, all with diabetes duration of at least 16 years. Two of these three were receiving treatment for hypertension, and one was also treated with erythropoietin injections for associated anaemia. Seventeen subjects ≥ 14 y had an eGFR of ≥ 140 ml/min/1.73m2, suggestive of hyperfiltration.

2.9 Other complications

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One subject had hypothyroidism which was being treated. . One subject had experienced a severe hypoglycemia episode in the past resulting in severe cognitive and motor impairment. Three patients were recorded as having diabetic retinopathy, and five subjects had cataracts (two of whom also had retinopathy). Neuropathy (loss of vibration and light touch) was recorded in one subject.

3. Initial impact of Life for a Child Program HbA1c results at the start of the LFAC program in 2004-2005 were available for 57 subjects. Values ranged from 4.9 - 15% (30–140 mmol/mol), with mean ± SD 9.6 ± 2.2% (81 ± 24 mmol/mol). For six-month paired data, mean ± SD HbA1c at baseline was 9.4 ± 2.3% (79 ± 25 mmol/mol), and 8.1 ± 1.8% (65 ± 20 mmol/mol) (n = 29, p = 0.006 by one-sided paired t-test ). For 12-month paired data, mean ± SD HbA1c at baseline was 9.7 ± 2.1% (83 ± 23 mmol/mol), and 8.7 ± 2.5% (72 ± 27 mmol/mol) at twelve months (n = 36, p = 0.007 by one-sided paired t- test) – see Figure 3.

Figure 3: Initial impact at commencement of Life for a Child support

n = 29, p = 0.006 n = 36, p = 0.007

Discussion Globally the incidence rates of type 1 diabetes in children vary widely due to differences in genetic susceptibility, combined with inadequately understood but powerful and evolving environmental factors.[1-3] There have been no previous studies on type 1 diabetes incidence of in Bolivia. Rates vary substantially in Central/South American and other Hispanic populations. Estimates for

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Bolivia in the IDF Atlas[1] are extrapolated from a 1990-91 study in Lima, Peru, which found an incidence of 0.5 per 100,000 children <15 y/y.[2] Other studies in South America in the early 1990s (all <15 y) showed rates per 100,000 ranging from 0.1 in Caracas, Venezuela to 8.3 in Montevideo[2,3]. Countries with both recent and older data are seeing sharp rises in type 1 diabetes incidence – in Mexico from 3.4 (per 100,000) in 2000 to 6.2 in 2012 for young people <20 y in the Instituto Mexicano del Seguro Social (IMSS) health insurance service[14]; in Chile from 5.7 in 2006 to 12.1 in 2012 for < 20 y[15], with the sharpest increase in the <5 y age group; and in Brazil a trend for increased incidence in those aged <15 y from 1986 to 2006[16]. Further afield for Hispanic populations, rates (<15 y) are 20.6 in Spain (<15 y 1995- 2001)[1]; 13.2 in Portugal (<15 y, 1994-1998)[1]; and 14.1 in Hispanic Whites in the USA (< 15 y, 2002-3)[17], with a recent study showing an increase of 4.2% per year in 2003-2012 on numbers <20 y.[18] Some of the variance in South American populations is thought to be due to lower rates of type 1 diabetes in Central/South American indigenous peoples as compared to those of Hispanic White/mixed descent.[2,19] Larenas et al.[20] found 3.8 times higher rates in Caucasian Chileans than in Mapuche (native Chileans). Bolivia has, by a substantial margin, the highest proportion of indigenous peoples in Central/South America.[21] This lower rate in indigenous populations is likely largely genetic in origin due to differences in HLA haplotypes.[19,22,23] However, differing exposure to environmental factors may also be potent influencers: rates of type 1 diabetes have increased in many countries as standards of living have increased. Incidence rates were found to be higher in high socioeconomic communes in Santiago de Chile.[24] The observed type 1 diabetes rate in Cercado in this study – 2.2 per 100,000 children <15 y/y with an estimated ascertainment of 80%, giving an estimated incidence of 2.7 per 100,000 – is five times higher than the figure previously used for Bolivia (based on the Peruvian data from 1990-1.[2] It is likely that type 1 incidence is increasing in Bolivia, however further studies will be needed to confirm this. This is still a low incidence rate compared to global figures. The female preponderance seen in Bolivia is common in low incidence studies[25], and is believed to be due to fathers with type 1 susceptibility genes being more likely to survive and pass on diabetogenic genes than mothers, with father’s genes more likely to cause type 1 diabetes in female offspring and mothers’ genes to cause diabetes in male offspring. In addition it is thought that fathers’ genes may be more diabetogenic than similar genes in mothers.[26,27] Monogenic diabetes has been reported from various countries and it is likely that the child diagnosed at 3-months of age has this form of diabetes – genetic testing is being arranged. If there is a gene defect, alternate non-insulin therapy may be possible depending on the specific gene.[28] Like various other less-resourced countries[29] the Bolivian government health service does not cover the cost of care for people with diabetes at any age. Most families cannot afford the cost of care, which can be prohibitive in such countries for families on lower incomes[30], and this can translate to the premature death of the child or young adult with diabetes, as occurred once in this Bolivian cohort. Furthermore, in Bolivia there are very few paediatric endocrinologists and, due to its relative rarity, limited knowledge of type 1 amongst general paediatricians. Therefore, the support from a centre such as CvCD +/- LFAC is crucial for families

35 with limited resources. CvCD provides a multidisciplinary service of not just diabetology but also health professionals in ophthalmology, nutrition, psychology, social work, foot care and podiatry, physiotherapy and rehabilitation, laboratory services, and pharmacy. There is also a young group or people with type 1 diabetes which encourage and support each other through meetings and use of the social media platform “WhatsApp”. The IDF Life for a Child Program provides insulin, and, since 2009, also provides blood glucose test strips, educational materials, and point-of-care HbA1c testing from Cochabamba. The initial impact seen in the LFAC follow-up data from 2004-5 has been sustained. Mortality is low at 2.3 per 1,000 patient years, and the mean/median HbA1c of 8.5/8.2% (69/62 mmol/mol) is surprisingly good, considering the substantial challenges faced in caring for these young people. Twenty-seven percent of those < 15 y and 28% of those 15-24 y were achieving the recommended HbA1c target of <7.5% (58 mmol/mol). This is not substantially different from the mean of 29/30% (male/female) for <15 y, and 24/20% (male/female) for 15-24 y in a large international study in which 15 of 16 countries were high income nations.[31] The higher HbA1c values seen in adolescents/emerging adults are similar to other reports[32], and likely reflect lifestyle and behavioural factors and growth spurt related insulin resistance. As in other countries, thoughtful medical attention and support is warranted during this period, along with provision of insulin supply security. It is of great concern that three young people with diabetes required renal replacement therapy, and four others have substantial renal impairment (eGFR < 50 ml/1.73m2). Furthermore, 17 had hyperfiltration, which may be a risk factor for diabetic nephropathy, although recent evidence suggests this may not be the case.[33,34] The presence of ESRD at a young age suggests that blood glucose control must have been poor for some years, and we note that for most of the Bolivian subjects evaluated herein, regular self-blood glucose monitoring has only been possible since 2009. Anderzén et al.[35] has shown the importance of a good early start in terms of blood glucose control, if later complications are to be reduced. Further assessment should be done for early signs of nephropathy such as microalbuminuria and hypertension, with management (with ACE inhibitors or LDL-lowering ‘statin’ drugs) being informed by the forthcoming results of the Adolescent type 1 Diabetes cardio-renal Intervention Trial (ADDIT).[36] Given the number with renal complications, it is likely that a thorough systematic assessment would lead to more subjects being found with other microvascular complications such as neuropathy and retinopathy, for whom early intervention with risk factor control and increased screening rates are appropriate. The common cause of death of people with type 1 diabetes is cardiovascular disease, for which dyslipidaemia is a major risk factor, and is treatable, with significant LDL-C, cardiovascular event and mortality reduction with statins.[37] The substantial numbers with one or more lipid risk factors such as high triglycerides and total cholesterol and low HDL-cholesterol levels, combined with the suggestion of blood pressure elevation, these results raise the possibility that some patients have features of the metabolic syndrome, which is recognised in type 1 diabetes and associated with higher rates of diabetes vascular complications.[38,39] This ‘double diabetes’ may benefit from the addition of metformin to insulin and risk factor control[40], though clinical trials with vascular end-points are still awaited.

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The study has three other limitations. It is possible that with further study (autoantibodies, C-peptide, unfortunately not available in this clinical context), some of the subjects diagnosed with type 1 diabetes may be re-categorised as having type 2 diabetes. Secondly, HbA1c measurements were not standardised across clinics and so it is possible that results could be affected by the different methods used. Finally, the 80% ascertainment is an estimated figure, and Cercado Province may not be fully representative of Bolivia – incidence may vary in other parts of the country due to ethnic or socioeconomic factors.

Conclusion This study has estimated the incidence of type 1 diabetes in Bolivia, confirming that incidence is relatively low compared to many other countries. The results demonstrate that reasonable blood glucose control and low mortality can be achieved in many subjects in a low- resourced setting with international support. However, there is a significant risk of early long- term complications in some subjects, as evidenced by renal impairment and substantial levels of cardiovascular risk factors.

Acknowledgements: We acknowledge the dedicated efforts of all at Centro Vivir con Diabetes, the determination of all these young people with diabetes, and their families. We also thank the supporters of the IDF Life for a Child and Insulin for Life Programs and Rotary International (Rotary Club of Cochabamba Quillacollo, District 6940, and the Rotary Foundation). Finally we thank Sarah Garnett for helping with SD scores.

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8. The World Bank. World Development Indicators, Bolivia. Available at http://databank.worldbank.org/data/reports.aspx?source=2&series=SP.POP.GROW&cou ntry=BOL, accessed 20th April, 2017. 9. WHO child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: methods and development. Geneva: WHO; 2006. 10. De Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Org 2007;85:660-667. 11. National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents. The fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics 2004;114 (2 Suppl.):555–576. 12. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density cholesterol in plasma without use of the preparative ultracentrifuge. Clin Chem 1972;18:199-502. 13. Levey AS, Stevens LA, Schmid CH, Zhang Y, Castro AF(III), Feldman HI. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604-612. 14. Gómez-Díaz RA, Pérez-Pérez G, Hernández-Cuesta IT, Rodriguez-Garcia JdC, Guerrero- Lopez R, Aguilar-Salinas CA et al. Incidence of type 1 diabetes in Mexico: data from an institutional register 2000-2010. Diabetes Care 2012;35:e77 15. Garfias C, Borzutzky A, Cerda J, Ugarte F, San Martin Y, Escobar C et al. Dramatic increase in type 1 diabetes in Chilean children between 2006 and 2012. Pediatr Diabetes. 2014;15(Suppl 19):121. 16. Negrato CA, Dias JP, Teixeira MF, Dias A, Salgado MH, Lauris JR et al. Temporal trends in incidence of Type 1 diabetes between 1986 and 2006 in Brazil. J Endocrinol Invest 2010;33:373-377. 17. The Writing Group for the SEARCH Study for Diabetes in Youth Study Group. Incidence of diabetes in youth in the United States. JAMA 2007;297:2716-2724. 18. Mayer-Davis EJ, Lawrence JM, Dabelea D, Divers J, Isom S, Dolan L et al. Incidence trends of type 1 and type 2 diabetes among youths, 2002-2012. N Engl J Med 2017;376:1419-1429. 19. Collado-Mesa FC, Barceló A, Arheart KL, Messiah SE. An ecological analysis of childhood- onset type 1 diabetes incidence and prevalence in Latin America. Pan Am J Public Health 2004;15:388-394. 20. Larenas G, Montecinos A, Manosalva M, Barthou M, Vidal T. Incidence of insulin-dependent diabetes mellitus in the IX region of Chile: ethnic differences. Diab Res Clin Pract 1996;34(Suppl):S147-151. 21. Center for Latin American Studies, Georgetown University. Indigenous Peoples, Democracy and Political Participation. Available at http://pdba.georgetown.edu/IndigenousPeoples/demographics.html, accessed 20thth April, 2017. 22. Gorodezky C, Alaez A, Murguía A, Rodríguez A, Balladares S, Miriam Vazquez M et al. HLA and autoimmune diseases: Type 1 diabetes (T1D) as an example. Autoimmune Rev 2006;5:187-194.

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23. Giraudo Abarca F.S, Carrasco E, Codner E, Pérez-Bravo F. Genetic of type 1 diabetes (T1D) in South America. Pediatr Diabetes. 2014;15(Suppl 19):88. 24. Torres-Avilés F, Carrasco E, Icaza G, Pérez-Bravo F. Clustering of cases of type 1 diabetes in high socioeconomic communes in Santiago de Chile: spatio-temporal and geographical analysis. Acta Diabetol 2010;47:251-257. 25. Karvonen M, Pitkäniemi M, Pitkäniemi J, Kohtamäki K, Simola E, Tajima N et al. Sex- difference in the incidence of insulin-dependent diabetes mellitus. An analysis of the recent epidemiological data. Diab Metab Rev 1997; 13: 275-291. 26. Tuomilehto J, Podar T, Tuomilehto-Wolf E, Virtala E. Evidence for importance of gender and birth cohort for risk of IDDM in offspring of IDDM patients. Diabetologia. 1995;38:975-982. 27. Waldhör T, Schober E, Rami B, Tuomilehto J, the Austrian Diabetes Incidence Study Group. The prevalence of IDDM in the first degree relatives of children newly diagnosed with IDDM in Austria-a population-based study. Exp Clin Endocrinol Diabetes. 1999;107:323-327. 28. Rubio-Cabezas O, Hattersley AT, Njølstad PR, Mlynarski W, Ellard S, White N et al. The diagnosis and management of monogenic diabetes in children and adolescents. Pediatric Diabetes 2014: 15(Suppl. 20): 47–64. 29. Ogle GD, Middlehurst AC, Silink M. The IDF Life for a Child Program Index of diabetes care for children and youth. Pediatr Diabetes 2016;17:374-84. 30. Ogle GD, Kim H, Middlehurst AC, Silink M, Jenkins AJ. Financial costs for families of children with Type 1 diabetes in lower-income countries. Diabet Med. 2016;33:820-826. 31. McKnight JA, Wild SH, Lamb MJE, Copper MN, Jones TW, Davis EA et al. Glycaemic control of type 1 diabetes in clinical practice early in the 21st century: an international comparison. Diabet Med. 2015;32:1036–1050. 32. Clements MA, Foster NC, Maahs DM, Schatz DA, Olson BA, Tsalikian E et al. Hemoglobin A1c (HbA1c) changes over time among adolescent and young adult participants in the T1D exchange clinic registry. Pediatr Diabetes 2016;17:327-336. 33. Thomas MC, Moran JL, Harjutsalo V, Thorn L, Wadén J, Saraheimo M et al. Hyperfiltration in type 1 diabetes: does it exist and does it matter for nephropathy. Diabetologia 2012;55:1505-1513. 34. Chatzikyrkou C, Haller H. Hyperfiltration – a risk factor for nephropathy in T1DM? Rev Endocrinol 2012;8:385-386. 35. Anderzén J, Samuelsson U, Gudbjörnsdottir S, Hanberger L, Åkesson K. Teenagers with poor metabolic control already have a higher risk of microvascular complications as young adults. J Diabetes Complications. 2016 Apr;30(3):533-6. 36. The Adolescent type 1 Diabetes cardio-renal Interventional Trial Research Group. Adolescent type 1 Diabetes cardio-renal Intervention Trial (AdDIT). BMC Pediatrics 2009;9:79. 37. Cholesterol Treatment Trialists' (CTT) Collaborators, Kearney PM, Blackwell L, Collins R, Keech A, Simes J, Peto R et al. Efficacy of cholesterol-lowering therapy in 18,686 people with diabetes in 14 randomised trials of statins: a meta-analysis. Lancet 2008;371:117-25. 38. McGill M, Molyneaux L, Twigg SM, Yue DK. The metabolic syndrome in type 1 diabetes: does it exist and does it matter? J Diabetes Complications. 2008;22:18-23.

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39. Sibley SD, de Boer IH, Steffes MW, Brunzell JD; Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Research Study Group. Intra-abdominal fat and elevated urine albumin excretion in men with type 1 diabetes. Diabetes Care. 2007;30:1898-900. 40. Vella S, Buetow L, Royle P, Livingstone S, Colhoun HM, Petrie JR. The use of metformin in type 1 diabetes: a systematic review of efficacy. Diabetologia. 2010 May;53:809-820.

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8.3 Paper 3

Ahmadov GA, Govender D, Atkinson MA, Sultanova RA, Eubova AA, Wasserfall CH, Mack SJ, Lane JA, Noble JA, Ogle GD. Epidemiology of childhood-onset type 1 diabetes in Azerbaijan: incidence, clinical features, biochemistry, and HLA-DRB1 status. Diabetes Research Clinical Practice 2018:144:252-259.

Authors: *Gunduz Ahmad Ahmadov1,2,3 [email protected] 99412 568 8343 *Denira Govender4,5 [email protected] Mark Alvin Atkinson6,7 [email protected] Rumiyya Anvar Sultanova2 [email protected] Amalia Abdulla Eubova3 [email protected] Clive Henry Wasserfall6 [email protected] Steven John Mack8 [email protected] Julie Ann Lane8 [email protected] Janelle Annette Noble8 [email protected] Graham David Ogle4,9 [email protected] +61 2 9869 1416

*Indicates equal contribution to the paper and recognition as co-first author. 1Endocrine Centre, Binagadi, Baku City, Azerbaijan (+994 12 568 8343); 26th Children’s Hospital, Baku City, Azerbaijan (+994 12 467-95-89); 3Azerbaijan Medical University, Baku City, Azerbaijan; 4International Diabetes Federation Life for a Child Program, Glebe, NSW, 2037, Australia; 5Sydney Medical School, University of Sydney, Sydney 2006, Australia; 6Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA 32610; 7Department of Pediatrics, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA 32610; 8Children’s Hospital Oakland Research Institute, Oakland, CA, USA 94609; 9Diabetes NSW, Glebe 2037, NSW, Australia Corresponding author: Dr. Graham Ogle, [email protected]

Word Count: 3549 (text); Abstract: 194/200 Numbers of Figures (2) and Tables (1)

Abstract Aims: Determine the incidence and typology of diabetes in children in Azerbaijan. Methods: Clinical features, C-peptide, autoantibodies (glutamic acid decarboxylase 65 (GAD65) and islet antigen 2 (IA-2)), and HLA-DRB1 status were studied in 106 subjects <18 years of age who were recently diagnosed. 104 cases were consecutive. Incidence was determined for Baku and Absheron regions, where ascertainment is estimated to be essentially 100%. Results: 104 of the 106 (98%) were diagnosed with type 1 diabetes, one with type 2 diabetes and one with atypical diabetes. Type 1 diabetes incidence in Baku City and Absheron was 7.05

41 per 100,000 population <15 years per year. Peak age of onset was 10 years. There was a slight male preponderance (male:female 1.17:1), and no temporal association with seasons. Almost all type 1 diabetes subjects presented with classic symptoms including a high incidence (58%) of diabetic ketoacidosis. 86% presented with low C-peptide values (<0.13 nmol/L, <0.40 ng/mL) and 74% were positive for at least one type 1 diabetes-related autoantibody. Conclusions: Azerbaijan has a moderate type 1 diabetes incidence and clinical, biochemical and genetic features similar to that in European populations.

Key words: childhood diabetes; Azerbaijan, incidence, autoimmunity, HLA

Introduction Various types of diabetes are diagnosed in childhood. The most common is type 1 diabetes, but type 2 diabetes, monogenic diabetes, and other forms also occur (1). The observed incidence of type 1 diabetes in children varies considerably around the globe, from >60 to <1 case per 100,000 children <15 years of age in nations such as Finland and Venezuela, respectively (1). This is thought to be due to both genetic and environmental factors, which are not fully understood (2). However, little is known regarding the clinical characteristics of diabetes in Azerbaijan, a landlocked upper-middle income country on the eastern edge of Europe. Indeed, there are no previous published reports on incidence, prevalence, or the types of diabetes occurring in children in Azerbaijan aside from one publication in 2006 on genetic associations (3). In order to further understand the patterns and aetiology of diabetes in children in Azerbaijan, we conducted a prospective study of consecutive new cases of diabetes diagnosed in children and adolescents <18 years at a major diabetes centre in the capital, Baku City. This study investigated the demographic, clinical, immunological and biochemical features of diabetes patients, as well as HLA-DRB1 alleles of subjects enrolled in this cohort. This was performed with the belief that improved diagnosis of the disease could lead to marked improvements in disease management.

Materials and Methods 1.1 Study Site The study was conducted at The Endocrine Centre and 6th Children’s Hospital in Baku City, Azerbaijan. All procedures were approved by relevant Ethics Committees in Azerbaijan the United States, and Australia, and performed in accordance with the Declaration of Helsinki. Written informed consent was obtained for all subjects prior to enrolment in the study. HLA genotyping was performed at Children’s Hospital Oakland Research Institute with IRB approval.

1.2 Study subjects A total of 106 subjects <18 years of age at diabetes diagnosis were enrolled. The subjects included two diagnosed in November 2013 and then a consecutive series of all subjects seen at the study institutions that were diagnosed from the 1st March 2014 to 5th March 2015. The study institutions act as referral centres for the entire country. Date of assessment ranged from March 2014 to March 2015 with 48 (45%) study subjects assessed on the same day as diagnosis, 39

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(37%) within one week, 10 (9%) within one week to one month, 8 (8%) within one to six months, and one (1%) after six months (maximum 7 months). 200 control subjects were enrolled from the general population. Control subjects were non-diabetic and unrelated to the subjects with diabetes or to each other.

1.3 Demographic data Date of birth, sex, ethnicity, city and province of residence at time of diabetes diagnosis, date of diagnosis, as well as distance and travel time to The Endocrine Centre or 6th Children’s Hospital were recorded.

1.4 Clinical parameters Diabetes was diagnosed according to standard World Health Organisation criteria (4). Determination of the type of diabetes was made by the local investigator according to clinical features and history. The presence of polyuria, polydipsia, weight loss, malnutrition and ketoacidosis at the time of diagnosis were recorded. Ketoacidosis was defined as presence of hyperglycemia (blood glucose >11mmol/l (198 mg/dl), ketone bodies in blood and/or urine, and clinical features such as Kussmaul respirations and dehydration. The following information pertaining to diabetes care was also recorded for each subject: date of insulin commencement, commencement daily dosage of insulin and number of injections per day, type of insulin used, insulin storage method at homes, use of oral hypoglycaemic agents, and other medications or treatment. History of other medical conditions, and family history was also recorded. Body weight and height were measured by electronic scale and stadiometer respectively with subjects wearing light-weight clothing and without shoes. Body Mass Index (BMI) was then calculated. BMI standard deviation (SD) scores were calculated using the WHO standards for <5 years (5) and for >5-19 years of age (6).

1.5 Sample Collection Peripheral blood was collected by venepuncture into vacutainer tubes on the day of assessment, after an overnight fast. Serum samples were spun down immediately and stored in a -20oC freezer. For HLA genotyping, 40-200 microliters of blood from each diabetes subject were deposited into vials containing DNAgard Blood (BioMatrica Inc. San Diego, CA USA). The stabilization reagent was resuspended in the blood, then the mixture was dried before shipping. Approximately one millilitre of saliva was collected from each control subject and mixed with 0.5 millilitres of DNAgard Saliva (BioMatrica Inc. San Diego, CA USA) prior to shipping.

1.6 Biochemical parameters and Serology For diabetes subjects, blood glucose was measured by Bioscreen MS-200 (Erba Lachema, Brno, Czech Republic). HbA1c was measured using a Clover A1c analyser (Infopia, Anyang Gyeonggi- do, Republic of Korea). C-peptide was measured in Azerbaijan by ELISA (IBL, Hamburg, Germany) within 72 hours of blood collection. Glutamic acid decarboxylase 65 (GAD65) and islet antigen 2 (IA-2) autoantibodies, were measured from frozen serum samples by commercially available ELISA kits (IBL, Hamburg, Germany) in Azerbaijan. GAD65 and IA-2 autoantibodies were considered positive if levels were ≥30 IU/mL, according to manufacturer’s recommendation.

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While not directly entered from this site, similar ELISA formats have been challenged in Islet Autoantibody Standardization Programs with comparable sensitivity and specificity to radioimmunoassays (7).

1.7 HLA alleles DNA was extracted from blood samples of 106 children with diabetes and also from saliva (BioMatrica, Inc. San Diego, CA USA) from 209 controls. The samples were genotyped for HLA alleles with high-resolution genotyping technology at Children’s Hospital Oakland Research Institute in California. PCR products (amplicons) were generated from genomic DNA using DRB generic exon 2 454 fusion primers. The 454 fusion primers consist of a locus-specific primer on the 3’ end, a 10-bp multiplex ID (MID) tag, and an “A” or “B” 454-specific primer sequence on the 5’ end. The MID tag serves as a sample barcode recognized by the Conexio ASSIGN™ ATF genotyping software (version 1.1.0.35, Conexio Genomics, Freemantle, Western Australia). Amplicons were purified with AMPure beads (Becton Dickinson, Franklin Lakes, USA), quantified using the Quant-iT PicoGreen dsDNA reagent (Life Technologies, Foster City, USA), and mixed with capture beads after dilution. Individual DRB exon 2 amplicon molecules were captured by these beads, amplified in an emulsion PCR and DNA-containing beads, and subsequently analyzed by pyrosequencing to obtain sequence readings originating from a single molecule (8- 9). HLA sequence data were generated using next-generation sequencing on the Roche 454 GS Junior System (Roche, Basel, Switzerland) and analyzed using Conexio ASSIGN™ ATF to interpret HLA genotypes from the sequence files (8-9).

1.8 Statistics Statistics were performed and graphs created using Excel software. Locus-level tests of heterogeneity and variant-level chi-squared ( 2) tests of association between 104 type 1 diabetes subjects and 200 control subjects were performed for the HLA-DRB1 locus using BIGDAWG R package (10). Hardy-Weinberg equilibrium (HWE) proportions of HLA-DRB1 genotypes in type 1 diabetes subjects and control subjects were tested using PyPop (v0.8.0) (11). We tested the significance of locus-level HWE deviations using Guo and Thompson’s exact method (12), and identified individual genotypes deviating significantly from HWE expectations using Chen’s method (13-14), using a threshold of significance of 0.05.

Results 2.1 Diagnosis 104 of the 106 enrolled diabetes patients were diagnosed as having type 1 diabetes. One female who presented at 8.1 years, with overweight, a positive family history, and acanthosis nigricans was diagnosed with type 2 diabetes. One female who presented with typical symptoms and ketonuria aged 11.6 years was diagnosed as having atypical diabetes as there was no overweight, and insulin was discontinued after three months and she was managed on glimepiride.

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2.2 Incidence During the 12-month period March 2014 to February 2015, 100 subjects were diagnosed with new onset type 1 diabetes, with 91 (91%) of these <15 years of age. Forty-three of these were living in the Baku region (the capital) or the region of Absheron which surrounds Baku. Using Azerbaijan government population data (15), Baku and Absheron were calculated to have an incidence of 7.05 per 100,000. Ascertainment in these two regions is thought to be 100% or very close to that, as all new diagnoses in these two regions are referred to Children’s Hospital No. 6.

2.3 Demographic characteristics Of the 104 subjects with type 1 diabetes, 56 (54%) were males and 48 (46%) were females. There was no discernible seasonal pattern in disease incidence (data not shown). All subjects were ethnic Azeris. The mean ± SD age of type 1 diabetes diagnosis was 8.9±4.4 years (range 1.0-17.3 years; Figure 1). The median age at diagnosis was 9.3 years and the peak age of onset was 10 years. 25.0% were diagnosed at 0-4 years, 32.7% from 5-9 years, 33.7% from 10-14 years and 8.7% from 15-17 years of age. When examining all enrolled subjects with diabetes (n=106), 13 (12%) subjects lived <10km from the hospital, 29 (27%) between 50-100 km, 13 (12%) 100-200 km, and 51 (48%) travelled more than 200km to access tertiary care.

Figure 1: The age of onset of type 1 diabetes in children <18 years in Azerbaijan

14

12

10

8

6

cases of Number 4

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

Age (years) n=104

2.4 Clinical parameters 2.4.1 Type 1 Diabetes cases (n=104) The main symptoms preceding diagnosis of type 1 diabetes were polyuria (n=104, 100%), polydipsia (n=104, 100%) and weight loss (n=103, 99%). Sixty (58%) subjects presented in diabetic ketoacidosis (DKA). DKA rates were 42.3% in the 0-4 year age group, 84.8% in the 5-9 year group, 52.8% in the 10-14 year group and 33.3% in the 15-19 year group. For those living

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in Baku City, the rates were 61.7% as compared to 54.4% outside the capital. Table 1 shows the relationships of DKA, C-peptide, and autoantibodies.

Table 1: The relationships of diabetic ketoacidosis, C-peptide and autoantibodies for 104 type 1 diabetes subjects.

C-peptide Autoantibody status C-peptide C-peptide C-peptide 0.13-0.26 0.26-0.56 <0.13 Both Either/both Neither nmol/L nmol/L GAD ≥ IA2 ≥ nmol/L autoantibodi autoantibodi autoantibodi (0.40- (0.80- 30 30 (<0.40 es es es 0.80 1.70 (n=64) (n=41) ng/mL) (n=28) (n=77) (n=27) ng/mL) ng/mL) (n=89) (n=8) (n=7) Diabetic 42 25 Ketoacidosis 50 (83%) 7 (12%) 3 (5%) 19 (32%) 48 (80%) 12 (20%) (70%) (42%) (n=60) C-peptide <0.13 nmol/L 54 33 23 (26%) 64 (72%) 25 (28%) (<0.40 ng/mL) (61%) (37%) (n=89) C-peptide 0.13-0.26 6 4 nmol/L (0.40- 2 (25%) 8 (100%) 0 (0%) (75%) (50%) 0.80 ng/mL) (n=8) C-peptide 0.26-0.56 4 4 nmol/L (0.80- 3 (43%) 5 (71%) 2 (29%) (57%) (57%) 1.70 ng/mL) (n=7)

For 104 patients diagnosed with type 1 diabetes, the mean±SD BMI was 15.5±2.7 (range 9.9-30.7). BMI SD scores ranged from -6.10–2.61 (mean = -1.06). Three subjects had a BMI SD >2, with a range of 2.07-2.61; all three had at least one type 1 diabetes-related autoantibody. Two subjects had a BMI SD of <5.0, ranging from -5.53 to -6.10. Both had at least one type 1 diabetes-related autoantibody and no signs of malnutrition. The mean±SD blood glucose at type 1 diabetes diagnosis was 24.0±8.0 mmol/L (range 9.4-44.4 mmol/L). Mean±SD HbA1c was 12.2±1.7% (108.7±19.1 mmol/mol) with a range 5.5-14.0% (range 36.6-129.5 mmol/mol).

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Three subjects (3%) had other significant medical conditions. One was diagnosed with both diabetes insipidus and type 1 diabetes at 2.3 years of age. This child was GAD65 positive, with no optic atrophy or deafness at the time of the study (Wolfram’s syndrome may still be possible). Another patient had Koolen-de Vries syndrome (17q21.31) and was positive for both type 1 diabetes–related autoantibodies. The third subject had Glucose-6-Phosphate Dehydrogenase Deficiency. Seven subjects with type 1 diabetes (7%) had a history of type 1 diabetes in the family: aunt (two subjects), sister (two), father (one), uncle (one) and cousin (one). All type 1 subjects were treated with insulin. 60 (58%) were on long acting insulin, 61 (59%) on short acting insulin, and 44 (42%) were on analogue insulin. 51 (49%) commenced on five injections per day, 45 (43%) four, and (8%) three. All but one subject had a refrigerator at home for insulin storage.

2.4.2 Other types of diabetes (n=2) The subject with type 2 diabetes (BMI SD 3.36) was treated with metformin and long acting insulin (one injection per day). The subject with atypical diabetes (BMI SD -1.13) was treated with glimepiride.

2.5 C-peptide For the 104 type 1 diabetes patients, the mean±SD fasting C-peptide was 0.11±0.10 nmol/L (0.32±0.31 ng/mL). Forty subjects (38.5%) had C-peptide ≤0.07 nmol/L (≤0.20 ng/mL). Eighty- nine subjects (86%) had values <0.13 nmol/L (<0.40 ng/mL), eight (8%) between 0.13-0.26 nmol/L (0.40-0.80 ng/mL) and seven (7%) between 0.26-0.56 nmol/L (0.80-1.70 ng/mL) (maximum C-peptide was 0.56 nmol/L (1.70 ng/mL)) (Figure 2). The relationship of C-peptide results with autoantibodies and the presence of DKA are shown in Table 1. C-peptide was ≤0.07 nmol/L (≤0.20 ng/mL) in 18.6% of the 59 subjects aged 0-9 years, and 64.4% of the 45 subjects aged 10-19 years. The subject with type 2 diabetes had a C-peptide level of 0.53 nmol/L (1.60 ng/mL), and the subject with atypical diabetes had 0.06 nmol/L (0.18 ng/mL) circulating C- peptide.

2.6 Autoantibody status For the 104 subjects with type 1 diabetes, 41 (39%) were IA-2 positive, 64 (62%) were GAD65 positive, 77 (74%) had either or both antibodies, and 28 (27%) were positive for both (see Table 1 for other relationships). GAD65 positivity was found in 74.6% of the 59 subjects aged 0-9 years, and 46.7% of the 45 subjects aged 10-19 years. Among autoantibody positive subjects, the mean±SD titer for IA-2 was 112.3±186.9 IU/mL and for GAD65 was 138.6±168.5 IU/mL. Autoantibodies were not detected in the subject with type 2 diabetes, but the subject with atypical diabetes was positive for IA-2 autoantibodies.

2.7 HLA results While the DRB1 genotypes of the 200 control subjects conformed to expected HWE proportions, those of the 104 diabetes subjects deviated significantly from HWE (p-value < 1E-05). The primary contributor to this deviation was an excess of DRB1*03:01+DRB1*04:02 heterozygotes

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(24 observed; 15 expected; p-value = 3.4E-03). DRB1*04:05 homozygotes were also observed to be in excess (3 observed; 0.5 expected; p-value = 7.1E-03), as were DRB1*09:01+DRB1*07:01 heterozygotes (3 observed; 0.25 expected; p-value = 6.0E-04). In addition, the absence of DRB1*07:01+DRB1*03:01 heterozygotes was also significant (0 observed; 3.75 expected; p- value = 1.48E-02). Genotyping of the DRB1 locus identified 38 alleles present in the population. Association analysis with the BIGDAWG (10) revealed that 14 of these alleles were present in sufficient frequency to assess T1D association (Table 2). The remaining 24 alleles were binned for association analyses. Significant heterogeneity was observed between diabetes subjects and control subjects at the locus level (p-value < 2.22E-16). DRB1*03:01 and DRB1*04:02 showed the strongest positive association with disease (OR 5.06 and 4.47; p = 7.77E-13 and 2.27E-10, respectively). DRB1*04:05 was also positively associated (OR 3.53; p = 1.90E-03). Six of the remaining 11 alleles showed negative disease association (protection), including alleles in the “DR2” group, DRB1*15:01 and DRB1*15:02.

Table 2: The frequencies of HLA alleles for 104 type 1 diabetes subjects versus 209 controls.

DRB1 Allele Patient Control OR (95% CI) p value Significance Frequency Frequency (n) (n) 01:01 0.0385 (8) 0.0383 (16) 1.01 (0.37 - 9.91E-01 NS 2.54) 03:01 0.2885 (60) 0.0742 (31) 5.06 (3.08 - 7.77E-13 * 8.4) 04:02 0.25 (52) 0.0694 (29) 4.47 (2.67 - 2.27E-10 * 7.57) 04:04 0.0144 (3) 0.0311 (13) 0.46 (0.08 - 2.13E-01 NS 1.69) 04:05 0.0721 (15) 0.0215 (9) 3.53 (1.42 - 1.90E-03 * 9.3) 07:01 0.0625 (13) 0.0789 (33) 0.78 (0.37 - 4.58E-01 NS 1.56) 11:01 0.0144 (3 0.0789 (33) 0.17 (0.03 - 1.09E-03 * 0.56) 11:04 0.0144 (3) 0.0789 (33) 0.17 (0.03 - 1.09E-03 * 0.56) 13:01 0.0096 (2) 0.0646 (27) 0.14 (0.02 - 2.05E-03 * 0.57) 13:02 0.0144 (3) 0.0383 (16) 0.37 (0.07 - 1.01E-01 NS 1.31) 14:01 0 (0) 0.0526 (22) 0 (0 - 0.35) 7.56E-04 *

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15:01 0.0144 (3) 0.0694 (29) 0.2 (0.04 - 3.28E-03 * 0.65) 15:02 0.0048 (1) 0.0646 (27) 0.07 (0 - 6.53E-04 * 0.43) 16:01 0.0337 (7) 0.0335 (14) 1 (0.34 - 9.92E-01 NS 2.71) Binned 0.1683 (35) 0.0335 (14) 0.78 (0.49 - 2.63E-01 NS 1.23)

Discussion This study investigated the incidence as well as clinical, biochemical, and genetic characteristics of new onset diabetes in children in Azerbaijan. No type 1 diabetes incidence data have been published previously from Azerbaijan. The 2015 International Diabetes Federation (IDF) Atlas (16) estimated a type 1 diabetes incidence of 7.0 per 100,000 <15 years of age and a prevalence of 928 cases in those <15 years of age. These numbers are based on extrapolation from data (17) from the neighbouring country of Armenia. However, the Azeris are a Turkic population (18); hence, comparisons with other Turkic populations may be more appropriate. Data exists for two such populations, both nationwide – type 1 diabetes incidence of 10.8 per 100,000 children <18 years of age per year was reported in Turkey 2011-2103 (19), and 3.8 per 100,000 <15 years of age per year in Uzbekistan in 2014 (20). The incidence found in the current study was 7.05 per 100,000. It is also possible that a few cases die at type 1 diabetes onset and are misdiagnosed with another condition. Indeed, this is thought to occur in a number of less-resourced countries, including Azerbaijan (21), although it would be expected to be less likely in and near the capital. Almost all (98%) subjects in this study were diagnosed with type 1 diabetes. The pattern of type 1 diabetes of Azerbaijan is similar to that of European (1) and Turkic (19-20) populations in terms of the peak age of onset and corresponds with an almost uniform presence of classic symptoms (1). No seasonal pattern was identified in this study, unlike a previous report from Turkey where onset was more common in winter and autumn (22). A small female preponderance has been found in Turkey (19) and particularly in Uzbekistan (20). However, this Azerbaijan data showed a slight male excess, in agreement with the prior published series from Azerbaijan (3). The frequency of DKA at diagnosis varies widely around the world from 12-80% (23). This study’s rate of 57.7% is therefore relatively high on an international scale, although consistent with published rates of 50.8% (22) and 65.9% (24) from Turkey. Such high rates are of concern as there is a significant risk of death from DKA (25), and recent data suggest the possibility of long-term sequelae (26). In this study, almost half of subjects with diabetes (48%) travelled >200 km to access tertiary care. Rates of DKA were similar between those diagnosed in Baku City and those outside the capital. Successful educational interventions have reduced the incidence of DKA in Italy (27) and Australia (28). A poster campaign focused on health clinics and hospitals was distributed in Azerbaijan in 2012-13. This campaign used the six-icon poster developed by the IDF Life for a Child Program and the International Society for Pediatric and Adolescent Diabetes) (29). Further

49 awareness of the presenting symptoms and signs of diabetes in young people is needed in Azerbaijan to reduce these rates. In this study, 61.5% of type 1 diabetes patients were GAD65 autoantibody positive, and 39.4% were IA-2 autoantibody positive while 26.9% had both autoantibodies. C-peptide levels were low (30) in almost all type 1 diabetes cases (86% <0.13 nmol/L [<0.40 ng/mL]). Limited comparable information is available from other Turkic populations. In Turkey, Karaguzel et al. (31) found that 63% of children with type 1 diabetes at a mean age of 11.7 years and mean duration of 3.4 years were GAD65 autoantibody positive. Marandi et al. (32) found that 27.6% of newly diagnosed type 1 diabetes subjects aged under 20 years had antibodies against GAD65, and 94.1% of subjects had a C-peptide of <0.17 nmol/L (<0.50 ng/mL) in a mainly Azeri population in Northwest Iran. Rates of GAD65 autoantibody positivity and C-peptide values ≤0.07 nmol/L (≤0.20 ng/mL) in the current study were remarkably similar to those observed in the SEARCH Study in the United States (33). Indeed, rates of positivity for autoantibodies against GAD65 were 61.5% and 61.4%, respectively, and rates of low to undetectable C-peptide (≤0.07 nmol/L [≤0.20 ng/mL]) were 38.5% and 38.4%, respectively. HLA genotyping of this population reveals DRB1 alleles common to European descent populations as well as alleles common to Asian populations. The pattern of T1D association, showing disease susceptibility from “DR3” and “DR4” alleles, with protection from “DR2” alleles, is not unexpected when compared to most studies of European populations (34). Notable, however, is the fact that the “DR4” allele that is most predisposing is DRB1*04:02, rather than the DRB1*04:01 allele common in Europeans. Azeri diabetes subjects heterozygous for the DRB1*03:01 and DRB1*04:02 alleles and homozygous for the DRB1*04:05 allele are more common than expected, given the frequencies of these predisposing alleles in the Azeri population, suggesting a role for these specific allele-combinations in diabetes. Also notable is the presence of the common European “DR2” DRB1*15:01 and the common Asian “DR2” DRB1*15:02 in the same population. This allows direct comparison of the two alleles in a single population and shows that both alleles are extremely protective for T1D. A previous report of HLA association with type 1 diabetes, from the same diabetes center in Azerbaijan, was consistent with these results (3). Low-resolution HLA genotyping of DQA1 and DQB1 loci showed the strongest predisposing T1D effects for DQB1*02 (commonly found in haplotype with DRB1*03:01), DQA1*03, DQB1*03:02, and DQB1*03:04 (all commonly found in haplotype with DRB1*04 alleles. DQB1*06:02, DQB1*05:03, and DQB1*06:01, all of which are found in haplotype with DRB1*15:xx or 16:xx alleles were found to be T1D protective, as was DQB1*03:01, also protective in European populations. A small study with low-resolution genotyping on patients and controls from southeast Turkey reported a strong predisposing effect for DQB1*02 and for the presumed haplotype DRB1*03-DQB1*02 (35). DQB1*03 was reported as significantly protective; however, the low- resolution genotyping of the study precluded distinction of the DQB1*03:01 (commonly type 1 diabetes protective) from the DQB1*03:02 (commonly type 1 diabetes predisposing) allele. Thus, the DRB1 results from this study are not inconsistent with lower-resolution genotyping results reported for similar populations.

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Of note, there was one subject (0.9%) who presented with type 2 diabetes and one subject (0.9%) with atypical diabetes. This latter case may prove to be type 1 diabetes with time, or may be monogenic in cause, but genetic testing has not been carried out. No cases were diagnosed prior to 1 year of age. Importantly, in this study, only two autoantibodies could be measured due to study funding; hence, there is a need to further evaluate the Azerbaijan population for additional type 1 diabetes-related autoantibodies including those against zinc transporter 8 (ZnT8) and insulin. In a handful of cases, we were unable to measure autoantibodies immediately at diagnosis, but the maximum duration of type 1 diabetes prior to study enrolment was seven months, which is unlikely to have significantly influenced results. HLA genotyping was resource-limited to a single locus (DRB1) for this report. More extensive analyses of HLA and minor type 1 diabetes susceptibility alleles (2) will reveal additional information regarding disease risk and heritability in Azerbaijan, and we intend to conduct these studies in the future.

Conclusions Diabetes in children in Azerbaijan is mainly type 1, although other types can occur. The incidence rate is mid-range in global terms. Clinical features at onset, autoimmunity, residual insulin secretion and HLA-DRB1 status are similar to European populations. It is our belief that data reported herein will likely aid future progress toward diabetes prediction, management, and education in Azerbaijan and other Turkic nations.

Data Availability The HLA-DRB1 data represent the first step of the comprehensive HLA class I and class II genotyping planned for this sample set. With the approval of the in-country investigators, and after publication of the data, the de-identified HLA will be provided to publicly available HLA databases, including allelefrequencies.net.

Conflicts of interest No potential conflicts of interest relevant to this article were reported.

Funding statement This study was partly funded by the Leona M and Harry B Helmsley Charitable Trust.

Acknowledgements The authors thank Angela Middlehurst for helping with the Ethics application, Amanda Posgai for her aid in composing the manuscript, Sarah Garnett for the BMI SD data, and Faizy Kakkat for assisting with the initial data analysis. We appreciate the support of IBL, who provided the ELISA kits at a reduced cost. The study was partially funded by the Leona M and Harry B Helmsley Charitable Trust. This work was also supported by National Institutes of Health (NIH) National Institute of Allergy and Infectious Disease (NIAID) grant R01AI28775 (SM). The content is solely the responsibility of the authors and does not necessarily reflect the official views of the NIAID, NIH or United States Government. None of the donors had any role in study design; in the

51 collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the article for publication.

Author contributions GA implemented the study in Azerbaijan and helped with writing the manuscript. DG did the data analysis and wrote the initial draft of the manuscript. MAA and CHW advised on the study protocol, implementation, and analysis and contributed to the manuscript. SM performed statistical analysis of HLA data and JL performed HLA genotyping. GDO designed and coordinated the study and co-wrote the manuscript. JN led the HLA analysis and co-wrote the manuscript.

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Immunol. 2016 Mar;77(3):283-287. doi: 10.1016/j.humimm.2015.12.006. Epub 2015 Dec 18. 11. Lancaster AK, Single RM, Solberg OD, Nelson MP, Thomson G. PyPop update--a software pipeline for large-scale multilocus population genomics. Tissue Antigens. Apr 2007;69 Suppl 1:192-197. 12. Guo SW, Thompson EA. Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics. Jun 1992;48(2):361-372. 13. Chen JJ, Thomson G. The variance for the disequilibrium coefficient in the individual Hardy-Weinberg test. Biometrics. Dec 1999;55(4):1269-1272. 14. Chen JJ, Hollenbach JA, Trachtenberg EA, et al. Hardy-Weinberg testing for HLA class II (DRB1, DQA1, DQB1, and DPB1) loci in 26 human ethnic groups. Tissue Antigens. Dec 1999;54(6):533-542. 15. The State Statistical Committee of the Republic of Azerbaijan. (2017, July 26). Population. Retrieved February 10, 2018, from https://www.stat.gov.az/source/demoqraphy/?lang=en. 16. International Diabetes Federation. IDF Diabetes Atlas (7th ed.) Brussels: International Diabetes Federation 2015. 17. Navasardyan L.V. Epidemiology of type 1 diabetes in children and adolescents in the Republic of Armenia. The New Armenian Medical Journal 2014;8:89-94. 18. West, BA. Azerbaijanis: nationality. Encyclopedia of the Peoples of Asia and Oceania. Infobase, 2009, pp. 68-72. 19. Yeşilkaya E, Cinaz P, Andıran N, Bideci A, Hatun Ş, Sarı E, et al. First report on the nationwide incidence and prevalence of type 1 diabetes among children in Turkey. Diabet Med 2016 Jan 27. doi: 10.1111/dme.13063. [Epub ahead of print]. 20. Rakhimova GN, Alimova NU, Ryaboshtan A, Waldman B, Ogle GD, Ismailov SI. Epidemiological data of type 1 diabetes mellitus in children in Uzbekistan, 1998-2014, Pediatr Diabetes, 2017 doi:10.1111/pedi.12495. 21. Ogle GD, Middlehurst AC, Silink M. The IDF Life for a Child Program Index of diabetes care for children and youth. Pediatr Diabetes 2016: 17: 374–384. 22. Ardicli D, Kandemir N, Alikasifoglu A, Ozon A, Gonc N. Clinical characteristics of type 1 diabetes over a 40 year period in Turkey: secular trend towards earlier age of onset. J Pediatr Endocrinol Metab. 2014 Jul;27(7-8):635-41. doi: 10.1515/jpem-2013-0320. 23. Usher-Smith JA, Thompson M, Ercole A, Walter FM. Variation between countries in the frequency of diabetic ketoacidosis at first presentation of type 1 diabetes in children: a systematic review. Diabetologia. 2012 Nov;55(11):2878-94. doi: 10.1007/s00125-012- 2690-2. Epub 2012 Aug 30. 24. Demirbilek H, Özbek MN, Baran RT. Incidence of type 1 diabetes mellitus in Turkish children from the south-eastern region of the country: a regional report. J Clin Res PediatrEndocrinol. 2013;5:98-103. 25. Rewers A. Current concepts and controversies in prevention and treatment of diabetic ketoacidosis in children. Curr Diab Rep. 2012 Oct;12(5):524-32.

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26. Cameron FJ, Scratch SE, Nadebaum C, Northam EA, Koves I, Jennings J et al. Neurological consequences of diabetic ketoacidosis at initial presentation of type 1 diabetes in a prospective cohort study of children. Diabetes Care 2014;37:1554-1562. 27. Vanelli M, Chiari G, Ghizzoni L et al. Effectiveness of a prevention program for diabetic ketoacidosis in children. An 8 year study in schools and private practices. Diabetes Care 1999;22:7-9. 28. King BR, Howard NJ, Verge CF et al. A diabetes awareness campaign prevents diabetic ketoacidosis in children at their initial presentation with type 1 diabetes. Pediatric Diabetes 2012;13:647-651. 29. International Diabetes Federation, & Life for a Child. (n.d.). DKA Prevention . Retrieved December 10, 2017, from http://www.lifeforachild.org/about/education- resources/dka-prevention.html. 30. Jones AG, Hattersley AT. The clinical utility of C-peptide measurement in the care of patients with diabetes. Diabet Med. 2013 Jul; 30(7): 803–817. Published online 2013 Jun 23. doi: 10.1111/dme.12159. 31. Karagüzel G, Şimşek S, Değer O, Ökten A. Screening of diabetes, thyroid, and celiac diseases- related autoantibodies in a sample of Turkish children with type 1 diabetes and their siblings. Diabetes Res Clin Pract. 2008 May;80(2):238-43. doi: 10.1016/j.diabres.2007.12.007. Epub 2008 Jan 31. 32. Marandi LY, Rajaii M, Aliasgarzadeh A, Sadeghi-Bazargani H. Islet cell autoantibodies in patients younger than 20 years of age with recently diagnosed diabetes in Northwest of Iran. Int J Diabetes Dev Ctries. 2011 Apr; 31(2):70-75. 33. Writing Group for the SEARCH for Diabetes in Youth Study Group, Dabelea D, Bell RA, D'Agostino RB Jr, Imperatore G, Johansen JM, et al. Incidence of diabetes in youth in the United States. JAMA. 2007 Jun 27;297(24):2716-24. 34. Erlich H, Valdes AM, Noble J, Carlson JA, Varney M, Concannon P, et al. HLA DR-DQ haplotypes and genotypes and type 1 diabetes risk: analysis of the Type 1 Diabetes Genetics Consortium families. Diabetes. 2008 Apr;57(4):1084-92. doi: 10.2337/db07- 1331. Epub 2008 Feb 5. 35. Keskin M, Aygün A, Pehlivan S, Keskin Ö, Kor Y, Balat A, et al. Trends in the frequency of HLA DR-DQ haplotypes among children and adolescents with type 1 diabetes mellitus in the southeast region of Turkey. J Clin Res Pediatr Endocrinol. 2012 Dec;4(4):189-92. doi: 10.4274/jcrpe.768.

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8.4 Paper 4

Fawwad A, Govender D, Ahmedani MY, Basit A, Lane JA, Mack SJ, Atkinson MA, Wasserfall CH, Ogle GD, Noble JA. Clinical features, biochemistry and HLA-DRB1 status in youth-onset type 1 diabetes in Pakistan. Diabetes Research Clinical Practice 2019;149:9-17.

Authors: *Asher Fawwad1,2 [email protected] *Denira Govender3,4 [email protected] Mohammad Yakoob Ahmedani2 [email protected] Abdul Basit2 [email protected] Julie Ann Lane5 [email protected] Steven John Mack5 [email protected] Mark Alvin Atkinson6,7 [email protected] Clive Henry Wasserfall6 [email protected] Graham David Ogle3,8 [email protected] Janelle Annette Noble5 [email protected]

*Indicates equal contribution to the paper and recognition as co-first author

1Biochemistry Department, Baqai Medical University, Gadap, Karachi, Pakistan 2Baqai Institute of Diabetology and Endocrinology, Nazimabad, Karachi, Pakistan 3Life for a Child, Glebe, NSW 2037, Australia 4Sydney Medical School, University of Sydney, NSW 2006, Australia 5Children’s Hospital Oakland Research Institute, Oakland, CA, USA 94609. 6Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA 32610. 7Department of Pediatrics, College of Medicine, Diabetes Institute, University of Florida, Gainesville FL, USA 32610. 8Diabetes NSW, Sydney, Australia

Corresponding author: Dr. Graham Ogle, [email protected]

Word Count: main body 3,852 Numbers of Figures (1) and Tables (2) plus one Supplementary Table

Abstract Published information on diabetes in Pakistani youth is limited. We aimed to investigate the demographic, clinical, and biochemical features, and HLA-DRB1 alleles in new cases of diabetes affecting children and adolescents <22 years of age. The study was conducted at Baqai Institute of Diabetology and Endocrinology in Karachi from June 2013-December 2015. One hundred subjects aged <22 years at diagnosis were enrolled. Demographic characteristics, clinical information, biochemical parameters (blood glucose,

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HbA1c, C-peptide, glutamic acid decarboxylase 65 (GAD65) and islet antigen 2 (IA-2) autoantibodies) were measured. DNA from 100 subjects and 200 controls was extracted and genotyped for HLA-DRB1 using high-resolution genotyping technology. Ninety-nine subjects were clinically diagnosed as type 1 diabetes (T1D) and one as type 2 diabetes (T2D). Of the 99 with T1D, 57 (57.6%) were males and 42 (42.4%) females, with mean age at diagnosis 11.0±5.2 years (range 1.6-21.7 years) and peaks at six and fifteen years. Fifty- seven subjects were assessed within one month of diagnosis and all within eleven months. For the subjects diagnosed as T1D, mean C-peptide was 0.63±0.51 nmol/L (1.91±1.53 ng/mL), with 16 (16.2%) IA2 positive, 53 (53.5%) GAD-65 positive, and 10 (10.1%) positive for both autoantibodies. In T1D patients, the allele DRB1*03:01 demonstrated highly significant T1D association (p < 10-16), with no apparent risk conferred by DRB1*04:xx alleles. Conclusions: Heterogeneous forms of T1D appear more common in children and youth in Pakistan than in European populations. Individual understanding of such cases could enablie improved management strategies and healthier outcomes. Key words: childhood diabetes, Pakistan, HLA, autoantibody, C-peptide

Introduction Youth onset diabetes has multiple etiologies with varied geographic distribution (1,2). Considering this variation, it is important to understand the pathophysiology in each part of the world. From this, education and training of healthcare professionals can be tailored to target the local situation. Furthermore, improved understanding of disease heterogeneity will enable the stakeholders to ensure the optimum utilisation of available resources. Little published information exists on diabetes in Pakistani young people, the sixth most populous nation in the world (3). Two incidence studies were performed in Karachi some years ago, in 1989-93 (4) and 1990-1999 (2), suggesting low incidence rates compared to Caucasian populations (2). Beyond this, Shera et al.(5) reported on clinical presentation and complications of a group of young people with type 1 diabetes (T1D) in Karachi, Pakistan’s capital, in 2008. There was also a small study on diabetes autoimmunity markers (6) which discusses the difficulty of distinguishing diabetes types. Finally, Lone et al. (7) reported on rates of diabetic ketoacidosis. We conducted a prospective study of 100 consecutive new cases of diabetes diagnosed in children and adolescents <22 years of age, investigating demographic, clinical, biochemical features, and HLA-DRB1 alleles. This study was conducted at the Baqai Institute of Diabetology and Endocrinology (BIDE) in Karachi, which was the first specialty-oriented diabetes centre to be established in Pakistan (8).

Methods 1.1 Study site The study was conducted at The Baqai Institute of Diabetology and Endocrinology (BIDE) in Karachi, Pakistan, which is a private tertiary care unit. All procedures were approved by relevant Ethics Committees in Pakistan, the United States, and Australia and were performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from all subjects prior to enrolment in the study. HLA-DRB1 genotyping was performed at Children’s Hospital Oakland Research Institute with IRB approval.

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1.2 Study subjects A total of 100 subjects <22 years of age at diabetes diagnosis were enrolled. All subjects were diagnosed in a consecutive series from June 23, 2013 to December 15, 2015. Date of biochemical assessment for this study ranged from December 30, 2013 to December 23, 2015 such that 14% were assessed on the same day as diagnosis, 19% within one week, 24% one week to one month, 32% one to six months and 11% after six months (maximum eleven months) from diagnosis. One patient was classified as having type 2 diabetes (T2D) after enrolment. Data for this patient was excluded from the genetic analyses. A set of 200 control subjects were collected as controls for the HLA genotyping studies. Inclusion criteria for the controls included 1) no diabetes, 2) both parents born in Pakistan, 3) not related to a T1D patient, and 4) not related to another control subject. Age and gender were not included and this detail was not revealed to the genotyping laboratory.

1.3 Demographic data Date of birth, sex, ethnicity, city and province of residence at diagnosis, date of diagnosis, distance from the clinic, as well as distance and travel time to the BIDE centre were recorded.

1.4 Clinical parameters Diabetes was diagnosed according to standard World Health Organisation (WHO) criteria (9). Determination of the type of diabetes was made by the local investigators according to available clinical features and history. The presence of polyuria, polydipsia, weight loss, malnutrition and ketoacidosis at the time of diagnosis were recorded. Ketoacidosis was defined as the presence of ketonuria as well as acidosis (anion gap calculation and/or measurement of arterial blood gases). The following information pertaining to diabetes care was recorded for each subject: date commencement of insulin, use of oral hypoglycaemic agents, and other medications or treatment. History of other medical conditions, and family history of type 1 diabetes were also recorded. Body weight and height at diagnosis were measured by electronic scales and stadiometer respectively, with subjects wearing light-weight clothing and without shoes. Body Mass Index (BMI) was then calculated. BMI SD scores were calculated using the WHO standards for those < 5 years of age (10), and for 5-19 years (11). For those 19-21 years of age, BMI SD was calculated using an age of 19.0 years.

1.5 Sample collection Peripheral blood was collected by venepuncture into vacutainer tubes on the day of assessment, after an overnight fast. Serum samples were spun down immediately and stored in a -20oC freezer. For genotyping, approximately 200ul of peripheral blood was preserved by mixing with DNAgard® blood (BioMatrica, San Diego, CA), then drying for storage and shipment. For controls, approximately 1 ml of saliva was mixed with DNAgard® saliva stabilizing reagent (BioMatrica, San Diego, CA) for storage and shipment.

1.6 Biochemical parameters and serology

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For diabetes patients, blood glucose was measured at diagnosis with a Selectra Pro S ELITech Group (Dieren, Netherlands). HbA1c was collected on the day of study assessment, and assayed using a BioRad D-10 analyser (Biorad Laboratories Inc., Hercules, USA). Fasting C-peptide and autoantibodies against glutamic acid decarboxylase 65 (GAD65) and islet antigen 2 (IA-2) were measured from frozen samples by commercially available ELISA kits (IBL, Hamburg, Germany) in Pakistan. Fasting C-peptide was measured in ng/mL. GAD65 and IA-2 autoantibodies were considered positive if levels were ≥30 IU/mL based on the standard curve, according to manufacturer’s recommendation. Similar ELISA formats have been challenged in Islet Autoantibody Standardization Programs with comparable sensitivity and specificity to radioimmunoassays (12).

1.7 HLA-DRB1 genotyping Blood samples collected from patients and saliva samples from controls were preserved using DNAgard® reagents from BioMatrica, Inc. (San Diego, USA). DNA was extracted from preserved blood and saliva samples using QIAamp® blood kits (Qiagen). The samples were genotyped for HLA-DRB1 alleles with high-resolution genotyping technology at the Children’s Hospital Oakland Research Institute in California. HLA sequence data for DRB1 exon 2 were generated using next- generation sequencing on the 454 GS Junior System (Roche, Basel, Switzerland) and on the MiSeq® platform (Illumina, San Diego, CA). For the Roche 454 platform, PCR products (amplicons) were generated from genomic DNA using DRB generic, exon 2 454 fusion primers. The 454 fusion primers consist of a locus- specific primer on the 3’ end, a 10-bp multiplex ID (MID) tag, and an “A” or “B” 454-specific sequence on the 5’ end. Amplicons were purified with AMPure beads (Becton Dickinson, Franklin Lakes, USA), quantified using the Quant-iT PicoGreen dsDNA reagent (Life Technologies, Foster City, USA), and mixed with capture beads after dilution. Individual DRB exon 2 amplicon molecules were captured by these beads and amplified in an emulsion PCR. DNA-containing beads were pyrosequenced on the 454 GS Junior instrument to obtain sequence reads originating from a single molecule (13,14). For the Illumina platform, DNA samples were amplified with primers containing the same locus-specific sequence used for the 454 platform but containing adapters to allow a second round of amplification. The second round of amplification served to attach individual “barcode” identifiers and sequences specific for sequencing on the Illumina platform. Second- round amplicons were purified and quantified as above, then mixed in equal proportions before sequencing on the MiSeq instrument. DRB1 genotype calls for data generated on the Roche 454 platform were assigned with a combination of two customized software packages: Assign™ ATF (Conexio Genomics, Freemantle, Western Australia) and Sequence COmpilation and REarrangement (SCORE™) software (Graz, Austria) (15). Genotype calls for data generated on the Illumina MiSeq platform were assigned using HLA Twin™ software, version 2.1 (Omixon, Budapest, Hungary).

1.8 Statistics The data were assessed for bimodality using likelihood ratio tests for nested finite mixture models. Models were fitted using an Expectation-Maximisation algorithm implemented in R

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3.3.1 (R Core Team, Vienna, Austria) and with the package ‘mixtools' (16). Significance was assessed using Wilks’ chi-square approximation and by parametric bootstrap with 1,000 samples. To assess sensitivity to distributional assumptions, the analysis was performed in triplicate, assuming mixtures of Normal, LogNormal and Gamma populations in turn. Locus-level tests of heterogeneity and allele-level chi-squared (2) tests of association between T1D subjects and control subjects were performed for the HLA-DRB1 locus using the BIGDAWG R package (17). Alleles were analysed at the two-field (peptide) level. For each allele-level comparison, alleles with expected counts less than 5 in cases or controls were combined into a common “binned” category for analysis (18). Hardy-Weinberg equilibrium (HWE) proportions of HLA-DRB1 genotypes in T1D subjects and control subjects were tested using PyPop (v0.8.0) (19). The significance of locus-level HWE deviations was tested using Guo and Thompson’s exact method (20), and individual genotypes deviating significantly from HWE expectations were identified using Chen’s method (21,22), using a threshold of significance of 0.05. Graphs were created using Microsoft Excel software.

Results 2.1 Diagnosis Ninety-nine of the 100 enrolled diabetes patients were diagnosed as having T1D. One male who presented at 11.9 years of age was diagnosed with T2D.

2.2 Demographic characteristics The 99 subjects with T1D included 57 (57.6%) males and 42 (42.4%) females. There was no discernible seasonal pattern in disease incidence (data not shown). 61.6% were of Muhajir ethnicity, 13.1% Sindhi, 10.1% Pashtun, 8.1% Punjabi, 2.0% Balochi and 5.1% other ethnic groups. The mean±SD age of diagnosis of T1D was 11.0±5.2 years (range 1.6 - 21.7 years). The median age at diagnosis was 11.0 years (Figure 1) with a suggestion of two peaks, the first at 6- 10 years and the second at 12-16 years. On bimodality analysis, the binary mixture model was significantly preferred to the single population model (p<0.05) using both the Wilks’ chi-square approximation and parametric bootstrap tests. We report the model with the most favourable Bayesian Information Criterion. Under this model, 48% of the data come from a Normal distribution with mean 6.4 and SD 2.7, and 52% from a Normal distribution with mean 15.2 and SD 2.8.

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Figure 1. The age of onset of T1D in young people <22 years of age in Pakistan.

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10

8

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Numberofcases 4

2

0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Age (years)

Fifteen subjects (15.2%) were diagnosed at 0-4 years, 31 (31.3%) from 5-9 years, 29 (29.3%) from 10-14 years, 20 (20.2%) from 15-19 years and 4 (4.0%) 20-21 years. Of all 100 subjects, 41 (41%) travelled <10km to access care, 42 (42%) 10-50 km, 4 (4%) 50-200 km and 13 (13%) >200km.

2.3 Clinical parameters The main symptoms preceding T1D diagnosis were polyuria (n=98, 99.0%), polydipsia (n=97, 98.0%) and weight loss (n=99, 100%). Twenty-one (21.2%) presented in diabetic ketoacidosis (DKA). For the 91 subjects with T1D who had both weight and height measured at diagnosis, the mean±SD BMI was 16.5±3.3 (range 10.2-27.3). Mean BMI standard deviation score (SDS) ranged from -7.41 to +2.61 (mean= -1.04). Two subjects had a BMI SDS > 2: 1) 2.61 in a boy aged 5 years with height SD -0.25, no DKA, both autoantibodies negative, and C-peptide 0.40 nmol/L (1.2 ng/mL) and 2) 2.27 in a boy aged 5 years with height SD -3.72, no DKA, both autoantibodies negative, and C-peptide 0.53 nmol/L (1.6 ng/mL). Two subjects had a BMI SDS < -5.0: 1) -6.18 in a boy aged 14 years with height SD -2.33, with malnutrition, DKA present, autoantibodies negative, C-peptide 0.40 nmol/L (1.2 ng/mL); and 2) -7.41 in a girl aged 16 years with height SD -1.80, malnutrition, no DKA, autoantibodies negative, C-peptide 0.93 nmol/L (2.8 ng/mL). For T1D subjects, the mean±SD blood glucose at diagnosis was 28.7±6.3mmol/L (range 13.6-45.9 mmol/L). The mean±SD HbA1c was 12.7±2.7 % (115.0±29.4 mmol/mol), with a range 7.1-21.0 (range 54.1-206.0 mmol/mol).

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Four T1D subjects had other medical conditions: two with cerebral palsy, one with thalassaemia (diagnosed after the diagnosis of diabetes), and one with both cerebral palsy and thalassaemia, diagnosed after diabetes. One T1D subject had a sister with T1D. All T1D subjects were treated with insulin. Eighty-seven (87.9)% started on insulin on the same day as diagnosis, 10 (10.1%) within 1 week, and two (2.0%) within 2 weeks. The single case diagnosed with T2D was a boy diagnosed at 12.0 years with a BMI SD of 2.78 and a height SD of 2.07, no DKA, both autoantibodies negative, and C-Peptide 1.62 nmol/L (4.9 ng/mL). He was initially commenced on insulin but then moved to metformin.

2.3 C-peptide The mean±SD for C-peptide was 0.63±0.51 nmol/L (1.91±1.53 ng/mL). Of T1D subjects, 3 (3.0%) had a C-peptide value <0.13 nmol/L (<0.4 ng/mL), 9 (9.1%) between 0.13-0.26 nmol/L (0.4-<0.8 ng/mL), 64 (64.6%) between 0.26-0.66 nmol/L (0.8-<2.0 ng/mL), 13 (13.1%) between 0.66-1.03 nmol/L (2.0-<3.1 ng/mL), and 10 (10.1%) >1.03 nmol/L (>3.1 ng/mL). There was no relationship between C-peptide and duration of diabetes before assessment (r=0.0.7, p=0.5 on linear regression). Table 1 shows relationships with DKA and autoantibody status.

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Table 1. The relationships of diabetic ketoacidosis, C-peptide and autoantibodies for 99 T1D subjects.

2.4 Autoantibody results For T1D subjects, 16 (16.2)% were IA-2 autoantibody positive, 53 (53.5%) were GAD65 autoantibody positive, and 10 (10.1%) were positive for both autoantibodies (see Table 1 for further relationships). Amongst seropositive subjects, the mean±SD titre was 105.8±137.0 IU/mL for GAD65 autoantibodies and 74.7±198.8 IU/mL for IA-2 autoantibody levels. Table 1 shows relationships with DKA and C-peptide status.

2.5 HLA-DRB1 results HLA-DRB1 genotypes were generated successfully for 100 patients and 188 control subjects. Association analysis for 99 T1D patients and 188 control subjects is shown in Table 2.

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Table 2. Association of DRB1 Alleles with Type 1 Diabetes in Pakistani Patients and Controls Controls Patients OR 95% C.I. p-value Significance1 Allele Count Frequency Count Frequency DRB1*01:01 15 0.03989 8 0.04040 1.01 0.37 - 2.6 9.76E-01 NS DRB1*03:01 44 0.11702 101 0.51010 7.86 5.06 - < 2.22E- * 12.25 16 DRB1*04:03 16 0.04255 1 0.00505 0.11 0 - 0.75 1.18E-02 * DRB1*07:01 61 0.16223 12 0.06061 0.33 0.16 - 0.65 5.13E-04 * DRB1*09:01 9 0.02394 9 0.04545 1.94 0.67 - 5.62 1.60E-01 NS DRB1*10:01 21 0.05585 5 0.02525 0.44 0.13 - 1.22 9.38E-02 NS DRB1*11:01 27 0.07181 5 0.02525 0.33 0.1 - 0.9 2.08E-02 * DRB1*11:04 17 0.04521 2 0.01010 0.22 0.02 - 0.92 2.54E-02 * DRB1*13:01 31 0.08245 5 0.02525 0.29 0.09 - 0.77 7.22E-03 * DRB1*14:04 6 0.01596 13 0.06566 4.33 1.5 - 14.1 1.56E-03 * DRB1*15:01 26 0.06915 3 0.01515 0.21 0.04 - 0.69 4.99E-03 * DRB1*15:02 32 0.08511 2 0.01010 0.11 0.01 - 0.44 2.96E-04 * Binned 71 0.18883 32 0.16163 0.83 0.51 - 1.33 4.19E-01 NS Total 376 198

OR: Odds Ratio CI: Confidence Interval Binned: Alleles with expected counts less than five in cases or controls were combined into a common “Binned” category for analysis, as described in Methods section 1.9. Counts and frequencies for all detected alleles are included in Supplementary Table S1. 1: The p-values for DRB1 alleles were not corrected for the number of comparisons, as the DRB1 locus displayed significant overall heterogeneity (p-value < 2.22E-16 ). Significant p-values are indicated with asterisks. NS. Not significant Total: The total number of alleles identified in controls and patients is shown in the last row.

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Supplementary Table S1. DRB1 Allele Counts and Frequencies (f) in Pakistani Type 1 Diabetes Patients and Controls

Allele Controls (N) Patients (N) Controls (f) Patients (f) Binned?1 DRB1*01:01 15 8 0.03989 0.0404 N DRB1*01:02 1 0 0.00266 0 Y DRB1*03:01 44 101 0.11702 0.5101 N DRB1*04:01 5 9 0.0133 0.04545 Y DRB1*04:02 7 7 0.01862 0.03535 Y DRB1*04:03 16 1 0.04255 0.00505 N DRB1*04:04 4 2 0.01064 0.0101 Y DRB1*04:05 2 3 0.00532 0.01515 Y DRB1*07:01 61 12 0.16223 0.06061 N DRB1*08:01 6 0 0.01596 0 Y DRB1*08:02 1 0 0.00266 0 Y DRB1*08:03 1 1 0.00266 0.00505 Y DRB1*08:04 1 2 0.00266 0.0101 Y DRB1*09:01 9 9 0.02394 0.04545 N DRB1*10:01 21 5 0.05585 0.02525 N DRB1*11:01 27 5 0.07181 0.02525 N DRB1*11:03 2 0 0.00532 0 Y DRB1*11:04 17 2 0.04521 0.0101 N DRB1*12:02 7 1 0.01862 0.00505 Y DRB1*13:01 31 5 0.08245 0.02525 N DRB1*13:02 8 3 0.02128 0.01515 Y DRB1*14:01 13 0 0.03457 0 Y DRB1*14:03 2 0 0.00532 0 Y DRB1*14:04 6 13 0.01596 0.06566 N DRB1*14:07 0 1 0 0.00505 Y DRB1*14:10 1 0 0.00266 0 Y DRB1*15:01 26 3 0.06915 0.01515 N DRB1*15:02 32 2 0.08511 0.0101 N DRB1*15:04 1 0 0.00266 0 Y DRB1*15:06 4 2 0.01064 0.0101 Y DRB1*16:01 3 0 0.00798 0 Y DRB1*16:02 2 1 0.00532 0.00505 Y f: Frequency 1: Alleles with expected counts less than five in cases or controls were combined into a common “Binned” category for analysis, as described in Methods section 1.9.

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As expected, the association of the DRB1 locus with T1D was highly significant (p<2.22 x 10-16). The risk for T1D was primarily driven by the allele DRB1*03:01, which is part of the conserved DRB1*03:01-DQA1*05:01-DQB1*02:01 haplotype (sometimes abbreviated as DR3- DQ2). DRB1*03:01 was seen at 51% frequency in T1D subjects but only 12% in controls (OR= 7.86; 95% CI = 5.06-12.25; p<2.22 x 10-16). The less frequent DRB1*14:04 allele (observed in 6.6% of T1D subjects but only 1.6% of controls) also predisposed to T1D (OR = 4.33; 95% CI = 1.5-14.1; p=1.56E-03). Coincidentally, both alleles are roughly four times more frequent in T1D patients than controls (DRB1*03:01: 4.4x; DRB1*14:04: 4.1x). In Asians, DRB1*14:04 is commonly found in a haplotype with DQB1*05:01. This haplotype was not found to be significantly associated with T1D in the Type 1 Diabetes Consortium data (23), but is significantly positively associated with juvenile autoimmune thyroiditis in (24). Notably, the similar European haplotype DRB1*14:01~DQB1*05:01 exhibits a very strong protective association with T1D (23). As anticipated, the Asian allele DRB1*04:03 was significantly negatively associated with T1D. Other DRB1*04 alleles, particularly DRB1*04:01/02/04/05, which are usually positively associated with T1D, were rare in these data and not significantly predisposing for T1D. Of the T1D patients, 66.7% contained at least one copy of DRB1*03:01, and 35.4% were homozygous for the DRB1*03:01 allele. This is in stark contrast to the typical HLA association result seen in European-derived populations, where up to 40% of patients are heterozygous for DRB1*03:01 and DRB1*04:01/04:02/04:04/04:05/04:08 (23). While DRB1 genotype proportions of the control subjects comported to HWE expectations (p = 0.35), DRB1 genotypes in the T1D subjects displayed an overall HWE deviation (p = 4.6 x 10-05) characterized by an excess of homozygotes (39 observed, 27.57 expected, p = 0.03). In particular, a significant excess of DRB1*03:01+DRB1*03:01 homozygous genotypes (35 observed, 25.8 expected, p = 2.5 x 10-04) and significant decrease in DRB1*03:01 heterozygotes (31 observed, 49.5 expected, p = 8.6 x 10-03) was observed for T1D subjects. Deviations were not observed for these genotypes in control subjects (DRB1*03:01 homozygotes: 4 observed, 2.57 expected, p = 0.47; DRB1*03:01 heterozygotes: 36 observed, 38.85 expected, p = 0.65).

Discussion This study investigated the clinical, biochemical, and genetic characteristics of new and recent onset diabetes in children and youth in Pakistan. The pattern of age of onset of subjects diagnosed with T1D suggested a bimodal distribution with peak diagnosis at approximately six to nine years in age with a second peak occurring in the early teenage years, a finding similar to the pattern observed in some other studies (25,26). However, previous studies in Pakistan have reported the peak age of T1D onset as 10-14 years (2) and 10-12 years (4). The male excess seen in this study was also observed in Karachi by Shera et al. (5), and in some studies in northern India (27-29). However, Staines et al. (4) in Karachi found a slight female excess as did and some studies in northern India. Globally, low incidence countries tend to have a female excess (30). Understanding of T1D in Pakistan is hampered by the lack of recent incidence studies. The two past studies suggested low incidence rates: 1.0 cases per 100,000 children <17 years of age per year in Karachi between 1989-1993 (4), and 0.5 cases per 100,00 children <15 years of

65 age per year in Karachi from 1990-1999 (2) compared to rates of 4.2-40.9 in the European populations reported in the same period (2). In our study, most T1D subjects (61.6%) were from the Muhajir ethnic group, who came from northern India at the time of the partition with Pakistan in 1947. This group represents only 7.6% of Pakistan’s population (3) but in Karachi, it is estimated to be 50% of the population (31). The incidence of T1D can change in migrant populations. The reported incidences in Karachi (with 50% of Indian descent) are lower than those reported in India: 3.0 per 100,000 <15 years in Karnal (northern India) in 2008 (27,32) and 10.5 in 1991-1994 in Madras (southern India) (33). In children of South Asian migrants to the United Kingdom and Sweden, rates are substantially higher than those observed in Pakistan or northern India but less than those in children born to parents from the country of immigration. For example, in Yorkshire (United Kingdom), the rate was 14.7 per 100,000 children <15 years of age of South Asian parents compared to 21.5 for non-south Asians (34) and in Sweden, the rate in children of South Asians was 34% of that in children of parents born in Finland (with an overall rate of 29 per 100,000 <15 years of age) (35). Such data show the potent impacts of both genetic and environmental effects in incidence of T1D (1,36). In this cohort, all but one of the 100 patients were clinically diagnosed with T1D. However, the data suggest that those classified as T1D are a heterogeneous group, consisting of typical/classic T1D, atypical T1D, and possibly other forms of diabetes such as malnutrition- related diabetes and T2D. The rate of DKA at onset was 21.2%, which is relatively low by international standards (37). The two previous Pakistan studies reported markedly different rates: 57.2% (7) and 5.8% (5). The GAD65 autoantibody positivity of 54% and IA-2 autoantibody positivity of 16% (with 10.1% of all 99 cases having both autoantibodies) are also relatively low (38). Only 12.1% had a fasting C-peptide at diagnosis of 0.25 nmol/L (<0.8 ng/mL), which is typically the upper threshold for insulin requiring T1D (39) and in 10.1% of cases, the C-peptide was >1.03 nmol/L (>3.1 ng/mL). Such heterogeneity of those diagnosed with T1D could be partly due to incomplete characterisation. Further autoantibody studies, of insulin autoantibodies and particularly Zinc transporter 8 (ZnT8), could reveal unrecognised autoimmunity. Shivaprasad et al. (40) documented rates of 64.7%, 31.8% and 19.3% for GAD-65, ZnT8 and IA-2 autoantibodies, respectively, with one quarter of those positive for ZnT8 being negative for the other two autoantibodies. However, autoantibody rates lower than those seen in children of European descent are not uncommon in studies from India (41-45). Even in Western countries, some T1D patients are autoantibody negative; in the SEARCH study for instance, 15.6% of those who had diabetes and were insulin sensitive were autoantibody negative (46). C-peptide studies after the honeymoon period has passed could show whether some of these subjects just have a slowly- progressive T1D, T2D, or possibly a different type of diabetes that is neither T1D nor T2D. T2D occurs at lower BMIs in Asian as compared to European populations (47). According to the Second National Diabetes Survey of Pakistan in 2016-17, rates of T2D in adults ≥ 20 years of age in Pakistan are 26.3% (males 26.2% and females 26.3%) (48). The incompletely understood and possibly overlapping entities of malnutrition-related diabetes and fibrocalculous pancreatic disease (FCPD) (49) are seen in India and Bangladesh (41,42,49), but have not been reported

66 from Pakistan. None of the subjects in this study had the history of chronic abdominal pain that is characteristic of FCPD, although two subjects had a BMI SDS <5.0 and so it is possible that malnutrition was occurring. Complicating diagnosis further, these two conditions may also have autoantibodies (42). In a small study from northern Pakistan, Fatima et al. (6) found that distinguishing between T1D and T2D was difficult even when autoantibodies and insulin resistance were studied. For individual subjects, it is important to be able to recognise if diabetes is not a classic T1D pattern with very low insulin secretion. Inexpensive oral medicines such as metformin or gliclazide may be of added benefit in a subset of individuals. If good control can be achieved from such medicines, then insulin may not be needed. The T1D patients in this study seem to have an unusually high representation of DRB1*03:01, with more homozygotes than expected. Kelly et al. (50) studied the T1D immunological features in Indo-Aryan children, with both parents originally from Pakistan or Indian , residing in the UK and found that the DR3-DQ2 haplotype (DRB1*03:01- DQA1*05:01-DQB1*02:01) was significantly positively associated with T1D in this population, as it is in most populations (24). Rasmussen et al. (51) examined HLA in newborns of Pakistani migrants in Norway to look for DR-DQ haplotypes considered to confer high-risk for T1D. They found the DR3-DQ2 haplotype in high frequency (18.5%); no instances of DR3/4 heterozygotes with a predisposing DR4 (expectation would be 2 or 3), and an excess of DR3/DR3 homozygous individuals (n =13, with expectation of 6). These data are somewhat consistent with the results presented here; however, because the study was of newborns, diabetes status was unable to be determined. Data from a population of Somali immigrants to the United States were quite similar to our Pakistani data in that nearly all of the T1D susceptibility was attributable to DRB1*03:01. Nearly every patient genotype (93%) included at least one DRB1*03:01 allele, and 50% of patients were homozygotes for DRB1*03:01 (52). One interpretation of this observation could be that the Pakistani and Somalian populations may partly share a common ancestry and genetic predisposition for T1D. Further genotyping of the HLA region as well as other T1D susceptibility loci in both populations will address this issue. Funding constraints limited this study to two autoantibodies (GAD65 and IA-2), a single HLA gene (DRB1), and a one-time measurement of C-peptide, with no external quality control. When funds are identified, samples will be genotyped for all classical HLA loci. Expansion to include other autoantibodies (particularly ZnT8) (40) and other HLA and genetic loci (53) could reveal further information. Longitudinal studies of C-peptide and insulin requirements would help further discrimination of the types of diabetes occurring in this population. Another limitation is that C-peptide and autoantibodies were not always measured at diagnosis. Particualrly for C-peptide, this may have resulted in a few subjects being in the “honeymoon phase” with some recovery of insulin secretion. In conclusion, this study shows that children and adolescents diagnosed with type 1 T1D in Pakistan may be a heterogenous group, as GAD-65 and IA2 autoantibody positivity and low C-peptide values are less common than in populations of European ancestry. HLA-DRB1 shows highly significant T1D association, but the overall allele distribution and individuals allele associations differ from Europeans, with DRB1*03:01 showing exceptionally strong risk. If there

67 is greater heterogeneity, individualised assessment of atypical “T1D” cases could lead to improved management strategies and healthier outcomes.

Acknowledgements The authors thank Angela Middlehurst for helping with the ethics application, Amanda Posgai for her aid in composing the manuscript, Sarah Garnett for the BMI SD data, and Gabriel Gregory for helping with statistical analysis. We appreciate the support of IBL, who provided the ELISA kits at a reduced cost. This study was partly funded by the Leona M. and Harry B. Helmsley Charitable Trust, and was supported by National Institutes of Health (NIH) National Institute of Allergy and Infectious Disease (NIAID) grant R01AI28775 (SM). The content is solely the responsibility of the authors and does not necessarily reflect the official views of the Leona M. and Harry B. Helmsley Charitable Trust, NIAID, NIH or United States Government.

No potential conflicts of interest relevant to this article were reported.

AF, MYA and AB implemented the study in Pakistan and helped with writing the manuscript. DG did the data analysis and wrote the initial draft of the manuscript. MAA and CHW advised on the study protocol, implementation, and analysis and contributed to the manuscript. SM performed statistical analysis of HLA data, and JL performed HLA genotyping. GDO designed and coordinated the study and co-wrote the manuscript. JN designed and coordinated the genetic portion of the study, including sample collection, DRB1 genotyping, and HLA analysis, and co-wrote the manuscript.

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8.5 Paper 5

Zabeen B, Govender G, Hassan Z, Noble JA, Lane JA, Mack SJ, Atkinson MA, Azad K, Wasserfall CH, Ogle GD. Clinical features, biochemistry and HLA-DRB1 status in youth-onset type 1 diabetes in Dhaka, Bangladesh. Diabetes Research Clinical Practice 2019;158:107894.

Authors: *Bedowra Zabeen1 [email protected] *Denira Govender2,3 [email protected] Zahid Hassan4 [email protected] Janelle Annette Noble5 [email protected] Julie A Lane5 [email protected] Steven John Mack5 [email protected] Mark Alvin Atkinson6,7 [email protected] Kishwar Azad1 [email protected] Clive Henry Wasserfall6 [email protected] Graham David Ogle3,8 [email protected]

*Indicates equal contribution to the paper and recognition as co-first author 1Department of Changing Diabetes in Children, Bangladesh Institute of Research and Rehabilitation of Diabetes, Endocrine and Metabolic Disorders, Dhaka, Bangladesh. 2 Life for a Child Program, Diabetes NSW, Glebe, NSW 2037, Australia 3Sydney Medical School, University of Sydney, NSW 2006, Australia. 4Dept of Physiology and Molecular Biology, Bangladesh University of Health Sciences (BUHS), Mirpur-1, Dhaka, Bangladesh & Dept of Physiology, Tairunnessa Memorial Medical College, Gazipur, Bangladesh 5Children’s Hospital Oakland Research Institute, Oakland, CA, USA 94609. 6Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA 32610. 7Department of Pediatrics, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA 32610. 8Diabetes NSW, Sydney, Australia

Corresponding author: Dr. Graham Ogle, [email protected]

Word Count: 3,125 with reference spaces Numbers of Figures (1) and Tables (3) Key words: diabetes, children, Bangladesh, autoimmunity, HLA

Abstract Aims: Little information is published on diabetes in young people in Bangladesh. We aimed to investigate the demographic, clinical, and biochemical features, and HLA-DRB1 alleles in new cases of diabetes affecting Bangladeshi children and adolescents <22 years of age.

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Methods: The study was conducted at Bangladesh Institute of Research and Rehabilitation of Diabetes, Endocrine and Metabolic Disorders (BIRDEM) in Dhaka. One hundred subjects aged <22 years at diagnosis were enrolled. Demographic characteristics, clinical information, biochemical parameters (blood glucose, HbA1c, C-peptide, and autoantibodies against glutamic acid decarboxylase 65 (GADA) and islet antigen-2 (IA-2A) were measured. High-resolution DNA genotyping was performed for HLA-DRB1. Results: Eighty-four subjects were clinically diagnosed as type 1 diabetes (T1D), seven as type 2 diabetes (T2D), and nine as fibrocalculous pancreatic disease (FCPD). Of the 84 with T1D, 37 (44%) were males and 47 (56%) females, with median age at diagnosis 13 years (range 1.6-21.7) and peak age at onset 12-15 years. 85% of subjects were assessed within one month of diagnosis and all within eleven months. For subjects diagnosed with T1D, mean C-peptide was 0.46±0.22 nmol/L (1.40±0.59 ng/mL), with 9 (10.7%) IA-2A positive, 22 (26%) GADA positive, and 5 (6%) positive for both autoantibodies. Analysis of HLA-DRB1 genotypes revealed locus-level T1D association (p=6.0E-05); DRB1*04:01 appeared predisposing (p<3.0E-06), and DRB1*14:01 appeared protective (p=1.7E-02). Conclusions: Atypical forms of T1D appear to be more common in young people in Bangladesh than in European populations. This will be helpful in guiding more specific assessment at onset and potentially, expanding treatment options.

Key words: Childhood diabetes, Type 1 diabetes, Bangladesh, HLA, autoantibody, C-peptide

Introduction The vast majority of diabetes in children in European countries is classic type 1 diabetes (T1D) [1,2]. However, there is evidence from various non-European populations that other types of diabetes, including atypical forms of the disease, occur more frequently than in European communities [3–6]. There is limited published information on diabetes in young people in Bangladesh, the eighth most populous nation in the world [7]. Aside from classic T1D, type 2 diabetes (T2D) [8] and fibrocalculous pancreatic disease (FCPD) also occur [9,10], and preliminary work indicates that autoantibody-negative forms of diabetes may be common [11]. Knowledge of the types of diabetes that occur and concurrent clinical, biochemical, and genetic factors will help in health professional training, organisation of care, and optimal treatment for each child or adolescent affected. We conducted a prospective study of 100 consecutive new cases of diabetes diagnosed in Bangladeshi children and adolescents <22 years of age, investigating demographic, clinical, and biochemical features as well as genotype at HLA-DRB1 alleles.

Methods Study site. The study was conducted at the Bangladesh Institute of Research and Rehabilitation of Diabetes, Endocrine and Metabolic Disorders (BIRDEM) in Shahbagh, Dhaka, Bangladesh, which is part of the network of services provided by the Diabetes Association of Bangladesh [12]. All procedures were approved by relevant Ethics Committees in Bangladesh, the United States

74 and Australia, and were performed in accordance with the Declaration of Helsinki. Written informed consent was obtained for all subjects prior to enrolment in the study.

Subjects. A total of 100 subjects ≤22 years of age at diabetes diagnosis were enrolled. The subjects were diagnosed from September 2014 to May 2015. 10% were assessed on the same day as diagnosis, 36% within one week, 39% one week to one month, 15% one to six months. All subjects were of Bengali ethnicity. One hundred and eight-one control subjects were also enrolled solely for HLA-DRB1 analysis. They were unrelated to the study subjects and to each other, and did not have diabetes or a family history of T1D. All subjects were of Bengali ethnicity.

Demographic data. Date of birth, sex, ethnicity, city and province of residence at diagnosis, date of diagnosis, distance, as well as distance and travel time to the BIRDEM centre were recorded.

Clinical parameters. Diabetes was diagnosed according to standard World Health Organisation (WHO) criteria [13]. Determination of the type of diabetes was made by the local investigators according to available clinical features and history: T1D was diagnosed upon abrupt onset of typical symptoms of diabetes with insulin required from diagnosis, and no acanthosis nigricans. They were usually non-obese. T2D was considered in pubertal or older subjects who were overweight or obese, who usually did not initially need insulin for blood glucose control, often had a slower onset of symptoms or were asymptomatic, and exhibited acanthosis nigricans, dyslipidaemia, and a family history of the disease. FCPD was diagnosed if there was pancreatic calcification on X-ray or ultrasonography, as reported by a radiologist, in the absence of alcohol intake, hypercalcemia, or biliary duct stones. A history of abdominal pain was also frequent in FCPD patients. The presence of polyuria, polydipsia, weight loss, and ketoacidosis at the time of diagnosis were recorded. Ketoacidosis was defined as the presence of ketonuria, as well as acidosis (bicarbonate <15 mmol/l). The following information pertaining to diabetes care was also recorded for each subject: date of insulin commencement, insulin dosage, number of insulin injections per day, type of insulin used, insulin storage method at homes, use of oral hypoglycaemic agents, and other medications or treatment. History of other medical conditions and family history were also recorded. Body weight and height were measured by electronic scales and stadiometer respectively with subjects wearing light-weight clothing and without shoes. Body Mass Index (BMI) was then calculated. BMI SD scores were calculated using the WHO standards for patients < 5 years of age [14] and for those 5.0-19.0 years [15].

Sample collection. After an overnight fast, peripheral blood was collected by venepuncture into vacutainer tubes on the day of assessment. Serum samples were spun down immediately and stored at -20oC. For gentotyping, blood samples collected from patients and saliva samples from subjects selected as controls were preserved using DNAgard® reagents from BioMatrica, Inc. (San Diego, USA).

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Biochemical parameters and serology. For diabetes patients, blood glucose was measured using an Evolution 3000 machine (Biochemical Systems International, Arezzo, Italy). HbA1c was measured using a Clover A1c analyzer (Infopia Co. Ltd. Kyunggi, Korea). C-peptide and autoantibodies against glutamic acid decarboxylase 65 (GADA) and islet antigen 2 (IA-2A) were measured by ELISA as previously described[16] .

HLA-DRB1 genotyping. All 84 of the T1D patients and 109 of the 181 control samples were genotyped using previously described methods[16] .

Statistical Analysis. Demographic and biochemical data was analysed using Microsoft Excel (Redmond, USA). For HLA-DRB1 locus analysis in T1D subjects, we used two approaches to perform locus- level tests of heterogeneity (comparing all alleles in cases to those in controls) and allele-level chi-squared (2) tests of association (comparing each individual allele against the set of all others in cases and controls) [17]. The preferred method for chi-squared analyses of case- control contingency tables for highly polymorphic genetic loci, such as HLA, is to combine low frequency alleles into a single “binned” category [18] to ensure that fewer than 20% of expected counts are less than five [19]. The BIGDAWG R package [20] combines alleles with expected counts less than five in either cases or controls into the binned category. However, because some alleles in this dataset that were present only in cases or controls were binned by BIGDAWG, we performed a set of ‘manual’ analyses in which only alleles with expected counts less than three in cases or controls were binned. Results of BIGDAWG analyses had no expected counts less than five, while only 14% (4/28) of expected counts were less than five using our manual analyses, a percentage appropriate for 2 analysis. Because we applied both the BIGDAWG and manual approaches, significance for locus level (kx2) tests of association was evaluated at the 0.025 α-level. In cases where the threshold of significance is not met for kx2 tests, the p-values for 2x2 tests must be adjusted for the number of alleles (n) tested (0.05/n). Hardy-Weinberg equilibrium (HWE) proportions of HLA-DRB1 genotypes in T1D subjects and control subjects were tested using PyPop (v0.8.0) [21]. The significance of locus-level HWE deviations was tested using Guo and Thompson’s exact method [22], and individual genotypes deviating significantly from HWE expectations were identified using Chen’s method [17,23] with a threshold for significance of 0.05.

Results Diagnosis. Eighty-four of the 100 enrolled diabetes patients were diagnosed as having T1D, seven with T2D, and nine with FCPD (Table 1).

Demographic characteristics. Of the 84 subjects with T1D, 37 (44.0%) were males and 47 (56.0%) females. The mean ± SD and range of age of diagnosis are shown in Table 1. The median age at diagnosis was 13.0 years and the peak age of onset was 12-15 years (Figure 1). Three T1D subjects (3.6%) were diagnosed at 0-4 years, 11 (13.1%) from 5-9 years, 42 (50.0%) from 10-14 years, 23 (27.4%) from 15-19 years, and 5 (6.0%) 20-22

76 years. Table 1 shows the sex distribution and age of onset of the subjects diagnosed with T2D and FCPD. Of all 100 subjects with diabetes, 30 (30%) travelled <10 km to access care, 11 (11%) 10-50 km, 34 (34%) 50-200 km, and 25 (25%) >200 km.

Table 1: Demographic, clinical and biochemical characteristics

Figure 1: The age of onset of type 1 diabetes in young people <22 years of age in Bangladesh

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Clinical parameters. The main symptoms preceding diagnosis of T1D were polyuria (n=77, 91.7%), polydipsia (n=76, 90.5%) and weight loss (n=77, 91.7%). Eight (9.5%) presented in DKA. Table 1 shows the BMI SD results for each diagnosis group. For the T1D subjects, two had a BMI SDS >2: 1) 2.63 in a girl aged 12y with height SD 0.99, no DKA, GADA and IA-2A negative, and C- Peptide 2.05 ng/mL; and 2) 2.47 in a girl aged 13y with height SD -0.34, no DKA, GADA and IA- 2A negative, and C-Peptide 1.2 ng/mL. Blood glucose and HbA1c values at diagnosis are also shown in Table 1. No subjects reported any other significant medical conditions. All subjects with T1D and FCPD commenced insulin at diagnosis. Two subjects with T1D also received metformin. For the seven subjects with T2D, three were treated with metformin only, three with insulin only, and one with both insulin and metformin. Of the 96 who commenced insulin, 54 (56.3%) were on long-acting human insulin, 63 (65.6%) were on short- acting insulin, 20 (20.8%) on pre-mixed insulin, and 11 (11.5%) on analogue insulin. One (1.0%) was receiving four injections per day, six (6.3%) three injections, and 89 (92.7%) two injections. Of the 96 subjects receiving insulin, 49 (51.0%) were able to store insulin in a refrigerator at home, 7 (7.3%) in a refrigerator outside the home, and 40 (41.7%) using clay pot evaporative cooling [24].

C-peptide. Table 1 shows C-peptide levels for those with T1D, T2D and FCPD. Of the 84 subjects diagnosed with T1D, C-peptide levels were not measured in three of the subjects. For those with T1D, C-peptide was in the normal range (0.8-3.1 ng/mL (0.26-1.03 nmol/L)) in sixty-eight T1D subjects, with no subject having values higher than the normal range. All T2D subjects had C- peptide values in the normal range, with low and normal range values in FCPD subjects.

Autoantibody results. Table 1 shows the autoantibody values for each diagnostic group. Table 2 shows relationships between DKA and C-peptide status in the T1D subjects. One of the seven subjects diagnosed with T2D was positive for IA-2A (41.5 IU/mL), and none were positive for GADA. Two of the nine FCPD subjects had a positive IA-2A (43.7 and 37.7 IU/mL), with another subject being positive for GADA of 304.1 IU/mL (Tables 1 and 2).

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Table 2: The relationships of diabetic ketoacidosis, C-peptide and autoantibodies for 81 T1D subjects

HLA results. A total of 33 unique DRB1 alleles were observed (Table 3 column A). As shown in Table 3 column B, overall locus-level association with T1D calculated using our manual approach was significant (p=0.00003). The most significantly associated allele was DRB1*04:01, which is well-established as a T1D risk allele in European populations [25–27]. No controls were observed to carry this allele, precluding calculation of an odds ratio (OR). When the statistical method of adding a count of 0.5 to the zero-count cell was applied, the estimated T1D OR for DRB1*04:01 was >45 (Supplementary Table). As expected from other studies [20,25,28–30], DRB1*14:01 showed a highly-protective effect for T1D (OR=0.000; p=0.017); no diabetes patients were observed with this allele. Of note, the DRB1*15:01 allele, usually observed to confer almost complete dominant protection in European cohorts [25,28,31], was not significantly protective in these data, while the closely-related, Asian DRB1*15:02 allele was significantly protective (OR=0.584; p=0.0477). Three other alleles, DRB1*03:01, DRB1*12:02 and DRB1*13:01, were suggestive of association, but the p-values were not significant.

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Table 3: DRB1 gentoyping of Type 1 diabetes patients

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These data were also analyzed using BIGDAWG (Table 3 column C) [20]. As described in the Methods, BIGDAWG bins all alleles that do not have expected counts of 5 in either the patient or control groups. Due to the small sample size of the T1D patient cohort, 24 of 33 observed alleles were binned by BIGDAWG, including DRB1*04:01 and DRB1*14:01, which were significantly T1D-associated in the manual analysis. The BIGDAWG approach resulted in nominal locus-level significance (p=0.049), which does not meet the 0.025 threshold of significance after correction for multiple kx2 tests. The only nominally significant allele identified by BIGDAWG analysis was DRB1*15:02 (p=0.049), which does not meet the corrected 0.005 threshold of significance for multiple 2x2 tests.

Supplementary Table 1: T1D case-control analysis using modified counts for unobserved alleles

DRB1 T1D T1D Allele Patients Controls p-value Odds Ratio 95% CI 01:01 3 8 7.48E-01 0.803 0.135 - 3.387 03:01 9 9 9.02E-02 2.216 0.761 - 6.412 04:01 10 0.5 7.98E-06 45.678 5.040 - Inf 04:03 7 25 2.16E-01 0.585 0.209 - 1.428 04:05 5 7 4.55E-01 1.553 0.382 - 5.768 07:01 40 72 3.08E-01 1.256 0.788 - 1.991 10:01 12 18 3.17E-01 1.468 0.629 - 3.314 12:02 12 43 9.52E-02 0.570 0.267 - 1.145 13:01 2 14 9.33E-02 0.299 0.033 - 1.330 14:01 0.5 12 3.30E-02 0.087 0.000 - 0.762 14:04 7 10 3.95E-01 1.528 0.482 - 4.515 15:01 21 34 2.78E-01 1.376 0.728 - 2.521 15:02 20 68 4.69E-02 0.583 0.323 - 1.019 Binned 20 42 9.25E-01 1.028 0.552 - 1.866 Locus-level p-value 9.92E-05

The count data in the T1D Patients and T1D Controls columns are identical to those in the patient frequency (n) and control frequency (n) columns in Table 3C, with the exception that the 0 count values for DRB1*04:01 in controls and DRB1*14:01 in patients have been changed from 0 to 0.5. The p-value, Odds Ratio, and 95% CI columns represent the results of the manual analysis approach described in Methods. The locus-level p-value for this analysis is shown in the box at the bottom of the table.

Discussion The incidence of T1D in young people in Bangladesh is still being determined. The IDF Atlas [32] reports a rate of 3.0 per 100,000 children <15 years per year, as derived from a study in India

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[33], but this is a different population. Preliminary data from our group indicates that the incidence of T1D in Dhaka is substantially lower, but rising quickly [34]. This study of 100 new- and recent-onset cases of diabetes in Bangladeshi children and youth found that in addition to T1D, T2D and FCPD are also common representing 7% and 9% of diabetes in youth, respectively. In those diagnosed with T1D, the age of onset is later (mean 13y, peak 12-15y) than in European populations, C-peptide values were often not clinically low (i.e., below 0.26 nmol/L (0.8 ng/ml)) at diagnosis, and autoantibody negativity was common (70.2%). There is a suggestion of two peaks for T1D onset in Bangladesh– the first around 5-6 years and the second at 10-15 years. However, as this was not a consecutive series, this observation should be tested with a larger, consecutive series. A female preponderance for T1D was observed (male:female ratio=0.79). This is commonly seen in lower-incidence populations [35], and described in the preliminary data published by Balsa et al. [34]. Classic T1D is characterised by low C-peptide levels, autoantibody positivity, and the development of DKA unless diagnosis is made earlier. A number of the subjects clinically diagnosed with T1D in this study did not have these findings, and the rate of DKA was low at 10% [36]. This may be due to a higher incidence of atypical forms of diabetes, incomplete characterisation of these cases, or a combination of these reasons. Aside from T1D, a number of subjects in this series were diagnosed with FCPD (n=9) or T2D (n=7). FCPD has been extensively reported in adults and adolescents in Bangladesh, India, and other countries [8,10,37], but the cause is not well understood. An association with the incompletely-understood condition of “malnutrition-related diabetes” was thought to be likely, but more recent evidence suggests that this is not so [37]. Pancreatic calcification and abdominal pain are characteristic. T1D autoantibodies have been raised in some subjects with FCPD in some but not all studies [37,38], potentially reflective of pancreatic damage [37]. T2D is common in adults in Bangladesh [39], and cases in older children and adolescents have been reported [8]. Autoantibody-negative forms of T1D occur in many populations, but appear to be more common in India [4,38,40–42] and other non-European populations [6,16,43], and the insulin resistance of T2D can be seen in autoantibody-positive subjects [3,40,43]. Some studies have attempted to address this with subclassifications of “ketosis-resistant” diabetes [40], and type 1B (idiopathic) diabetes [4]. The fact that the overall DRB1 locus association was less strong in these data, compared to published results from other populations [31], supports the notion that the pathophysiology of T1D may differ in this population compared to more widely-studied populations, such as European and African cohorts [31,44]. The differences in results observed between the two association analyses performed on these data illustrate the challenges involved with analysis of highly-polymorphic HLA genotyping data. The possibility exists that the T1D-associated alleles detected in the manual analysis could be spurious, resulting from type 1 statistical error. However, the striking differences in control versus patient counts for DRB1*04:01 (0 vs. 10) and DRB1*14:01 (12 vs. 0), combined with the facts that these statistically-significant associations are seen for alleles with well-established T1D associations and that the associations are in the expected direction (i.e., DRB1*04:01 is predisposing [25–27] and DRB1*14:01 is protective [20,25,28–30]), argue that the detected associations are likely real. An alternative explanation is that these alleles occur at relatively low frequencies in this population, which could also help

82 explain the weak overall T1D association in this data set. BIGDAWG’s binning strategy may be overly conservative for a small population sample displaying a >2:1 difference in the number of controls and patients, and may result in type 2 statistical error (i.e., missing one or more true associations). In the present study, the diagnosis of the type of diabetes was made by clinical features, and the boundary between T1D/atypical T1D and T2D was difficult to determine without assessment of insulin sensitivity and further testing of C-peptide at intervals beyond diagnosis. Also, due to funding considerations, only two autoantibodies were studied: GADA and IA-2A. The addition of zinc transporter-8 autoantibodies (ZnT8A) [45] and insulin autoantibodies (IAA) may reveal further evidence of autoimmunity. Analysis of DQ and other HLA alleles would also provide further information, however this has not been possible to date due to funding constraints. In conclusion, distinguishing the type of diabetes in these non-classical “T1D” cases is not just of scientific interest. It is our experience that standard practice in many less-resourced countries is to start and continue such patients on insulin alone unless there are overt signs of T2D (in particular, obesity and acanthosis nigricans). In some cases though, oral agents, such as metformin or a sodium-glucose co-transporter 2 inhibitor may be of benefit. These subjects deserve to receive “personalised medicine”, with appropriate investigations taking into consideration the constraints of local resources.

Acknowledgements The authors thank Angela Middlehurst for helping with the Ethics application, Amanda Posgai and Jayanthi Maniam for their aid in composing the manuscript, and Sarah Garnett for the BMI SD data. We appreciate the support of IBL, who provided the ELISA kits at a reduced cost.

Funding The work performed in this study was partly funded by The Leona M. and Harry B. Helmsley Charitable Trust, and by National Institutes of Health (NIH) National Institute of Allergy and Infectious Disease (NIAID): R01AI28775 (SM) and P01AI42288 (MAA). The content is solely the responsibility of the authors and does not necessarily reflect the official views of the NIAID, NIH or United States Government.

Duality of Interests No potential conflicts of interest relevant to this article exist.

Author Contributions BZ, JN and KA implemented the study in Bangladesh and helped with writing the manuscript. DG conducted the data analysis and wrote the initial draft of the manuscript. MAA and CHW advised on the study protocol, implementation, and analysis and contributed to the manuscript. SM performed statistical analysis of HLA data and JL performed HLA genotyping. GDO designed and coordinated the study and co-wrote the manuscript. JN led the HLA analysis and co-wrote the manuscript.

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Guarantor Statement As the guarantor of this work, Graham David Ogle assumes full responsibility for the ethical collection, analysis and reporting of data as well as the decision to publish.

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haplotypes and genotypes and type 1 diabetes risk analysis of the type 1 diabetes genetics consortium families. Diabetes 2008. doi:10.2337/db07-1331. [31] Erlich H, Valdes AM, Noble J, Carlson JA, Varney M, Concannon P, et al. HLA DR-DQ haplotypes and genotypes and type 1 diabetes risk: analysis of the type 1 diabetes genetics consortium families. Diabetes 2008;57:1084–92. doi:10.2337/db07-1331. [32] IDF. Eighth edition 2017. 2017. doi:http://dx.doi. org/10.1016/S0140-6736(16)31679-8. [33] Kalra S, Kalra B, Sharma A. Prevalence of type 1 diabetes mellitus in Karnal district, Haryana state, India. Diabetol Metab Syndr 2010;2:14. doi:10.1186/1758-5996-2-14. [34] Balsa A, Zabeen B, Ogle G, Tayyeb S, Azad K. Incidence estimate of type 1 Diabetes in Youth in Dhaka. Endocrine Abstracts 2017); 49: EP428. Available at https://www.endocrine-abstracts.org/ea/0049/ea0049ep428.htm, accessed 23rd June, 2019. [35] Karvonen M, Pitkäniemi M, Pitkäniemi J, Kohtamäki K, Simola E, Tajima N et al. Sex- difference in the incidence of insulin-dependent diabetes mellitus. An analysis of the recent epidemiological data. Diab Metab Rev 1997; 13: 275-291. [36] Usher-Smith JA, Thompson M, Ercole A, Walter FM. Variation between countries in the frequency of diabetic ketoacidosis at first presentation of type 1 diabetes in children: A systematic review. Diabetologia 2012;55:2878–94. doi:10.1007/s00125-012-2690-2. [37] Unnikrishnan R, Mohan V. Fibrocalculous pancreatic diabetes (FCPD). Acta Diabetol 2015;52:1–9. doi:10.1007/s00592-014-0685-9. [38] Singh AK, Bhatia E, Dabadghao P, Bhatia V, Gellert SA, Colman PG. Role of islet autoimmunity in the aetiology of different clinical subtypes of diabetes mellitus in young north Indians. Diabet Med 2000;17:275–80. [39] Biswas T, A, Rawal LB, Islam SMS. Increasing prevalence of diabetes in Bangladesh: a scoping review. Public Health 2016;138:4–11. doi:10.1016/j.puhe.2016.03.025. [40] Goswami R, Kochupillai N, Gupta N, Kukreja A, Lan M, Maclaren NK. Islet cell autoimmunity in youth onset diabetes mellitus in Northern India. Diabetes Res Clin Pract 2001;53:47–54. [41] Tandon N, Shtauvere-Brameus A, Hagopian WA, Sanjeevi CB. Prevalence of ICA-12 and other autoantibodies in north Indian patients with early-onset diabetes. Ann N Y Acad Sci 2002;958:214–7. [42] Dayal D, Samprati M, Kaur N, Ranjana WM, Jayaraman D. Prevalence of Beta-Cell, Thyroid and Celiac Autoimmunity in North Indian Children with Recent Onset Type 1 Diabetes (T1D). J Clin Diagnostic Res 2015;9:1–2. doi:10.1111/pedi.12200. [43] Dabelea D, Pihoker C, Talton JW, D’Agostino RB, Fujimoto W, Klingensmith GJ, et al. Etiological approach to characterization of diabetes type: The SEARCH for diabetes in youth study. Diabetes Care 2011;34:1628–33. doi:10.2337/dc10-2324. [44] Noble JA, Johnson J, Lane JA, Valdes AM. HLA class II genotyping of African American type 1 diabetic patients reveals associations unique to African haplotypes. Diabetes 2013. doi:10.2337/db13-0094. [45] Shivaprasad C, Mittal R, Dharmalingam M, Kumar PK. Zinc transporter-8 autoantibodies can replace IA-2 autoantibodies as a serological marker for juvenile onset type 1

86 diabetes in India. Indian J Endocrinol Metab 2014;18:345–9. doi:10.4103/2230- 8210.131174.

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8.6 Paper 6

Ogle GD, Middlehurst AC, Silink M. The IDF Life for a Child Program Index of diabetes care for children and youth. Pediatric Diabetes 2016: 17: 374–384.

Authors: 1,2Graham D. Ogle, FRACP 1,2Angela C. Middlehurst, CDE 1,3Martin Silink, MD

From the 1International Diabetes Federation Life for a Child Program 2Diabetes NSW, Sydney, Australia 3Children’s Hospital at Westmead, Sydney, Australia

Corresponding author: Dr. Graham Ogle, [email protected]

Word Count: 5,240 (including 664 words in the requested Appendix and 878 words in Acknowledgements) Numbers of Figures (2) and Tables (2)

Abstract Background and Objectives: Care for children and youth with diabetes varies markedly around the world. We developed a standardised, reproducible measure that can be used to document and compare critical factors influencing treatment outcomes. Methods: A questionnaire consisting of 36 multiple-choice questions covering major components of care (such as insulin therapy, blood glucose monitoring etc.) was sent to 75 countries: 43 under-resourced countries where the International Diabetes Federation’s Life for a Child Program operates, and 32 others (mainly developed nations). Results for each country were scaled to a score with a range of 0-100. Results: Responses were received from 71 countries. Scores varied widely and were highly correlated to per capita gross domestic product (R2=0.72, P<0.001) and health expenditure (R2=0.77, P<0.001). For the 37 low- and lower-middle income countries, only two had full government provision of human insulin and none of blood glucose test strips. Marked differences according to income were also found for access to home refrigeration; usage of insulin pens, multiple daily injections, pumps, glucagon, and ketone strips; HbA1c testing; and complications screening. Conclusions: The Index is a comprehensive, easily-administered survey instrument. It demonstrated stark differences in access to numerous components of care necessary in achieving good outcomes for children and youth with diabetes.

Key words: childhood diabetes; developing countries; insulin; blood glucose monitoring; index

1. Introduction

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It is estimated that there are almost 500,000 children <15 years of age with diabetes [1,2], with a similar or even higher number of persons aged 15-25 years having this disease. Unfortunately, the care for children and youth with diabetes varies widely around the world. In many developed nations children and youth have full access to all components of care. In some other countries, quality care is inaccessible or unaffordable. Sadly, many children and youth with Type 1 diabetes die soon after diagnosis (or even before diagnosis, often misdiagnosed as another illness). Others often have poor diabetes control and frequently develop early and devastating complications. Multiple publications exist regarding the care in individual developed countries, with some studies [3,4] comparing care provided by centres in various developed nations. For less- resourced countries, clinical assessments have been published for a few countries such as Tanzania [5-6] and Rwanda [7]. The International Diabetes Federation (IDF) survey on insulin and diabetes supplies [8], and detailed diabetes health systems assessments conducted by the International Insulin Foundation in six countries [9-12]. However, these studies focus mainly on access, availability and cost of supplies of diabetes care overall, and do not cover a number of specific components related to childhood and youth diabetes care. Therefore we have developed an Index which covers essential components of diabetes care that influence outcomes for children and youth with diabetes, including insulin [13], monitoring of glycemic control [14], diabetes education [15], and complications screening [16]. The aim of the IDF Life for a Child (LFAC) Index of Diabetes Care for Children and Youth is to document the current global status of such components of care, and provide a standardised, reproducible measure that can be used to assess the availability of critical components of diabetes care which in turn influence outcomes. The Index highlights areas that deserve attention within countries and across regions, will assist with local and international advocacy, and can be used to monitor improvements in provision of care.

2. Methods 2.1 Development of survey instrument A questionnaire with 36 multiple-choice questions was developed by the investigators – two pediatric endocrinologists and one diabetes nurse educator, all with wide experience in diabetes care at all resource levels. The questions covered components of diabetes care that were grouped into five broad areas: insulin, other supplies, health professionals, organisation of care, and other components of care. See Appendix 1 for details. The questionnaire was reviewed by experts involved in multinational diabetes initiatives in Europe, Africa, and Asia. It was then piloted in two African and two Asian countries, refined according to the comments received, and finalised. Translations into French and Spanish were conducted by diabetes experts who were fluent in the respective languages.

2.2 Administration of survey The questionnaire was sent to 75 countries - all 43 countries supported by or about to commence support from the IDF Life for a Child Program, along with 32 other countries to provide a global picture.

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The survey was emailed to the key person(s) known to be fully aware of the standard of childhood and youth diabetes care in each country surveyed. The questionnaire was completed and returned by email. Two versions of the questionnaire were used – “Country” and “Clinic”. The two versions only differed on the replacement of “country” with “state/province” in the wording of the 23 questions, otherwise the content for all question did not alter. The “Country” questionnaire was used when it was thought that the respondent would be able to answer for the situation in the entire country. This version was sent to 66 countries. In 43 of these it was sent to the person known by LFAC to be involved in coordinating childhood and youth diabetes care within the main clinic in the country – generally the senior physician at the clinic, or otherwise the head of the local diabetes association (when the latter was directly involved in coordination of care). For 23 high- and upper-middle income countries with many leading clinics, the “Country” questionnaire was also used as there was generally homogenous provision of government services. The questionnaire was sent to a representative clinic coordinated by a recognised expert, known to LFAC, who was familiar with care across the respective country. The “Clinic” questionnaire was used in nine countries as it was known by the investigators that there was no specific leading clinic and furthermore, unlike in higher-income countries with more homogenous care, it was known that care varied markedly between the clinics. These countries were: Democratic Republic of Congo, Ecuador, Ghana, Liberia, Nigeria, Pakistan (each with 2 questionnaires sent and returned), Thailand (3), India (4) and Mexico (6). For each of these countries a mean score of each question was used in the overall analysis.

2.3 Developing the scale The minimum score for each question was 0, and the maximum score varied from 2 to 8 depending on the number of options. The minimum possible total raw score was 0 and the maximum 131. Raw scores for each question (from 0-2 to 0-8 depending on the number of options) were scaled to a score of 0-10. This provided a total score of 0-360. This total was then divided by 3.6 so as to be expressed as a score with a minimum of 0 and a maximum of 100.

2.4 Relationship to income levels and health expenditure Health Expenditure per capita, and Gross Domestic Product (GDP) per capita based on Purchasing Power Parity (PPP) in current international dollars was acquired for each country from the World Bank website [17] (generally 2012 data). The same source was accessed to classify all countries as Low Income, Lower-Middle Income, Upper-Middle Income or High Income. If World Bank data was not available, the CIA Factbook was used [18].

2.5 Statistical analysis Trend analysis across income levels was performed in SAS using the Cochran-Armitage test, adjusted using the Benjamini-Hochberg False Discovery Rate to control for multiple comparisons. Correlation was calculated by Pearson’s test. A p value of <0.05 was considered significant.

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3. Results The LFAC Index questionnaire was sent to 75 countries, with 71 of these returning the questionnaire (see Table 1). No response was received from four countries - China, Indonesia, Israel and South Africa. All 71 countries that returned the questionnaire completed all questions.

Table 1: Scaled LFAC Index Score (out of 100) for each country surveyed

Score Numbers of Countries (in alphabetical order) Countries 0-19 6 Burkina Faso, Burundi, Haiti, Liberia, Mauritania, Solomon Islands 20-39 20 Cambodia, Dominican Republic, Democratic Republic of Congo, Ecuador, Ethiopia, Gambia, Ghana, Guatemala, Guyana, Iraq, Jamaica, Kenya, Nepal, Nigeria, Papua New Guinea, Republic of Congo, Tajikistan, Togo, Vietnam, Zimbabwe 40-59 20 Azerbaijan, Bangladesh, Bolivia, Egypt, Eritrea, Fiji, India, Maldives, Mali, Mexico, Morocco, Pakistan, Philippines, Rwanda, Sri Lanka, Sudan, Tanzania, Thailand, Uganda, Uzbekistan 60-79 7 Bermuda, Botswana, Cayman Islands, Cuba, Malaysia, Montenegro, Romania 80-100 18 Australia, Czech Republic, Denmark, France, Germany, Hungary, Ireland, Italy, Japan, Korea, Luxembourg, Netherlands, New Zealand, Norway, Singapore, Sweden, United Kingdom, United States

3.1 Overall scores Scaled scores (maximum 100) ranged from 17.6-97.6 (mean 53.4). Table 1 shows the scaled score quintile for each country.

3.2 Domain results 3.2.1 Insulin Results for insulin provision in three age-groups - <15 years, 15-18 years, and 18-25 years were averaged as there was no significant difference when evaluated across age groups. 2.3% of countries had no government/non-government organisation (NGO) provision with insulin available only through private pharmacies, in 8.5% there was some provision through NGOs in one or more major centres only, in 5.2% there was some provision through government sources (GS) in one or more major centres only, in 19.7% provision in major centres and some regional areas by NGOs, in 16.9% provision in major centres and some regional areas by GS, in 7.5% full provision of human insulin by NGOs (+/- some GS), in 7.0% full provision of human

91 insulin by GS, in 9.4% full provision of human insulin and some provision of analog insulin by GS, and in 23.5% full provision of analog insulin by GS. At the institution that filled out the questionnaire, the most common insulin regimen was twice- daily pre-mixed insulin in 16 countries; twice-daily regular and NPH insulin in 18; multiple daily injections (3-4/day) of human insulin in nine; multiple daily injections of analog +/- human insulin in 21; and pump therapy in seven. Country-wide, the most common insulin regimen was twice-daily premixed insulin in 20 countries; twice-daily regular and NPH insulin in 20; multiple daily injections (3-4/day) of human insulin in six; multiple daily injections of analog +/- human insulin in 21; and pump therapy in four.

3.2.2 Other supplies For children < 15 years, there was no government provision of blood glucose meters and strips with few children monitored in nine countries, some provision through non-government sources in 33, full provision (two or more tests per day) by non-government sources in six, and full provision by government in 23. Results were similar in the 15-18 year age-group, with less government or non-government provision in some countries in the 18-25 year age group. In 12 countries there was no government support for syringes and limited access from other sources - families must buy syringes privately. There was some provision of syringes through non-government sources in 24, and full provision in seven. Five countries had full syringe provision by the government, six had full pen provision, seven had some government assistance with pumps and 10 full government assistance with pumps. Clinics in four countries had no access to HbA1c testing. Five countries had laboratory equipment only in the main clinic, 25 in the main and also in regional clinics. 20 had point-of- care testing in the main clinic alone and 17 also in regional clinics. In 12 countries families must pay all costs of medical care and laboratory testing. 12 had some support from non-government sources and 17 had support from government sources. Full support was available from non- government sources in 4, and from government sources in 26. More than 25% of families needed to travel long distances (>2 hours travelling time each way) for supplies and review in 29 countries. In 19 countries, 5-25% of families had long travel times, and in 23% of countries <5% of families had long travel times.

3.2.3 Health professionals The highest level of pediatric diabetes nurse training was a general nurse in 12 countries. There was a nurse with interest in diabetes in 14, a trained diabetes nurse educator in the major clinic in 19, and a trained diabetes nurse educator also in regional clinics in 26. 18 countries did not have any other health professionals in the diabetes care team. 14 had a dietician in the surveyed clinic, 16 had a dietician and social worker in the surveyed clinic, four also had dieticians in regional clinics, and 19 had dieticians and social workers in both the surveyed and also regional clinics.

3.2.4 Organisation of care

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There was no pediatric or adolescent clinic in 17 countries - children and youth were cared for within the adult clinic. Care was provided through pediatric clinic(s) in 34 countries, and a further 20 had a pediatric and also a transition clinic. The estimated proportion of children and youth receiving “standard care” at the surveyed clinic was <10% in 11 countries, 10-33% in six, 34-66% in nine, 67-95% in 13, and >95% in 32. The estimated proportion of children and youth receiving “standard care” across the country was <10% in 19 countries, 10-33% in 10, 34- 66% in 10, 67-95% in 11, and >95% in 21. 3.2.5 Other components of care There was no active diabetes association in three countries. Nine had an association which was not an IDF member, 21 had an association that was an IDF member not actively involved in meeting the needs of children and youth with diabetes, and 38 had a member association that was active in this way. No diabetes camps or activity days had been held in nine countries. 16 had education half-days or days in the past, 18 had occasional camp(s) and 28 had annual camps. There was no diabetes register or data collection in 13 countries. 35 had a limited register and data collection, eight had a comprehensive register and data collection in one region, and in 15 it was nationwide. 17 countries had no data on incidence, prevalence, or types of diabetes. 17 others had limited data that was not recent, 23 had limited recent data, and 14 had comprehensive data

3.3 Relationship to income levels and health expenditure The scaled score was evaluated against the log-plot of 2011 per capita health expenditure (HE) - see Figure 1A, (data not available for Bermuda); and GDP (PPP) – see Figure 1B. The R2 correlation to HE was = 0.77 (P<0.001), and for GDP (PPP) 0.72 (P<0.001). Table 2 shows the mean scaled scores for each country income level.

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Figure 1: Association between LFAC Index score and economic indicators (log plots).

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Legend: A: Index score compared to per capita Gross Domestic Product (Purchasing Power Parity). B: Index score compared to per capita Health Expenditure.

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Table 2: Scaled LFAC Index scores, and selected indicators, according to country income levels

Low Income Lower-middle Upper-middle High income P Countries Income income countries (n=19) countries countries (n=20) (n=18) (n=14)

Score (mean (range))

Scaled score (0-100) 31.8 (17.6- 39.1 (14.4- 51.4 (27.7- 88.1 (63.0- <0.0001 48.0) 59.7) 76.6) 97.6)

Insulin (number of countries / % of countries)

Multiple daily injections or 1 (5.3%) 2 (11.1%) 7 (50.0%) 19 (95.0%) <0.0001 pump therapy country-wide No duty on insulin 9 (47.3%) 7 (38.9%) 11 (78.6%) 15 (75.0%) 0.02

Other supplies (number of countries / % of countries)

Full syringe provision by 2 (10.5%) 3 (16.7%) 5 (35.7%) 18 (90.0%) <0.0001 government Use of insulin pens ≥10% 0 (0%) 1 (5.6%) 8 (57.1%) 20 (100%) <0.0001 (excluding pump therapy) Point of care HbA1c testing 7 (36.8%) 9 (50.0%) 4 (28.6%) 17 (85.0%) 0.01 in leading centre ≥5% children having urine or 2 (10.5%) 2 (11.1%) 3 (21.4%) 20 (100%) <0.0001 blood ketone strips at home Full government support for 1 (5.3%) 2 (11.1%) 6 (42.9%) 17 (85.0%) <0.0001 medical care and laboratory testing

Health professionals (number of countries / % of countries)

Trained diabetes nurse 11 (57.9%) 12 (66.7%) 4 (28.6%) 18 (90.0%) 0.15 educator in country

Organisation of care (number of countries / % of countries)

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Screening for eye 7 (36.8%) 12 (66.7%) 9 (64.3%) 20 (100.0%) <0.0001 complications regularly conducted in leading centre Screening for foot 6 (31.6%) 9 (50.0%) 7 (50%) 20 (100.0%) <0.0001 complications regularly conducted in leading centre (where clinically indicated) 67% or more of children in 4 (21.0%) 11 (61.1%) 10 (71.4%) 20 (100%) <0.0001 leading centre receiving standard care 67% or more of children in 3 (15.8%) 8 (44.4%) 8 (57.1%) 20 (100%) <0.0001 country receiving standard care Presence of 24-hour 6 (31.6%) 7 (38.9%) 6 (42.9%) 19 (95.0%) <0.0001 diabetes emergency call service

Other components of care (number of countries / % of countries)

Locally adapted education 7 (36.8%) 8 (44.4%) 8 (57.1%) 19 (95.0%) <0.0001 materials for children/youth Some or substantial 6 (31.6%) 4 (22.2%) 0 (0%) 19 (95.0%) <0.001 interaction between health professionals and teachers/schools

P values refer to relationship of the respective indicator to country income group (assessed by trend analysis).

The relationships of eight key indicators to country income level are shown in Figure 2. All demonstrated a strong (p<0.001) relationship to income level. Data on refrigeration was comparable to published country electrification rates [19]. The relationships of Country Income Level to other selected indicators are shown in Table 2.

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Figure 2: Relationships of key indicators to country income level.

A: Full provision by government of insulin for children <15 y. B: Full provision by government of 2+ test strips per day for children <15 y. C: Most common insulin regimen at major centre Multiple Daily Injections or pump therapy. D: >67% of families having access to a home refrigerator. E: >5% of children having glucagon at home. F: Pediatric endocrinologist in country. G: Screening for microalbuminuria regularly conducted at leading centre. H: Good knowledge in country re symptoms of diabetes, with deaths from misdiagnosis thought to be very unlikely. For all graphs, the number of countries is: low income (19), lower- middle income (18), upper-middle (14), and high income (20). P values refer to relationship of the respective indicator to country income group (assessed by trend analysis).

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For insulin, the lowest GDP and HE for countries where government health services could fully provide insulin was Vietnam ($3,265 and $95 respectively). Only four of the 53 countries with GDP <$10,000 could provide insulin (Vietnam, Fiji, Thailand and Egypt). Three countries of the 28 with GDP >$10,000 did not provide insulin. For HE, 12 of the 40 countries with HE >$100 did not provide insulin. Conversely, all 10 countries where governments provided full assistance with pumps had GDP (PPP) >$25,000 per annum). For meters and strips, the lowest GDP and HE for countries where government health services could fully provide meters and strips was Fiji ($4,493 and $168 respectively). Fiji was the only country of 53 with GDP <$10,000 that could provide strips. Six of the 28 countries with GDP >$10,000 did not provide strips. For HE, only two countries of the 46 with HE <$500 could provide strips (Fiji and Botswana), with 21 of 24 nations with HE >$500 providing strips.

4. Discussion 4.1 Key findings The LFAC Index demonstrates stark global differences in the availability of all components of diabetes care for children and youth. The instrument was easy to use, as demonstrated by the high response rate and full completion of questions. It identifies strengths and weaknesses within countries, and indicates areas that need attention on an individual country and regional level. Key benchmarks for provision of care are defined – such as affordable provision of insulin by governments to all in need, and provision of at least “standard care”. The results also provide baseline data that can be used as a benchmark to monitor progress over time – for instance on a second-yearly assessment. The Index will also be useful in lobbying and advocacy on both a national and global scale to strive for equity of care. The Index Score, and almost all key indicators were highly correlated to a country’s per capita GDP, and even more highly correlated to health expenditure. No government health service in any low-income country, and only a few in lower-middle income countries were able to provide human insulin (an essential medicine as defined by the WHO [20]) to all children in need, with fewer providing blood glucose test strips (at a very modest minimum level of two tests per day). Government provision of insulin syringes was often also poor. Access to glucagon and urine ketone strips was extremely low except for high-income countries (despite glucagon also being on the WHO Essential Medicines list [20]). The study reveals further challenges with insulin therapy in that many families do not have access to home refrigeration, with insulin losing its potency much more quickly in hot environments [21]. Deaths from misdiagnosis of diabetic ketoacidosis (DKA) are thought to be likely or very likely in most surveyed countries. The availability of other components of youth diabetes care – the full multidisciplinary team with a dietician and social worker, 24-hour telephone advice, diabetes camps, locally produced and relevant education materials, use of standardised international or national treatment guidelines, transition clinics from pediatric to adult care, professional associations, engagement of schools – varied markedly and generally only high income countries had most or all of these in place.

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4.2 Study limitations The major limitation of the study is that only one respondent was used in most countries. Whilst this respondent was the leading expert in all less-resourced countries and a leading expert in more resourced countries, it is possible that they were not aware of some variations in care within their country that may have led to different answers in one or more questions.

4.3 Key implications Without Government health system support, costs can be prohibitive for families. Health Action International conducted a snapshot survey of the price of a 10mL vial of 100 IU/mL insulin in 60 countries in 2010 [22]. The mean price varied from $13-24 depending on the manufacturer. For an adolescent with diabetes receiving 45-50 Units per day, an annual supply would be about 18 vials. Even at the lower price of $13 this would cost $234 per year. This study demonstrates that a number of nations still impose customs duty on insulin, needlessly elevating insulin prices. Blood glucose monitoring is even more costly - the annual cost of two test strips per day is $219-730 (based on LFAC internal data from country questionnaires). Given the high cost of supplies, even after eliminating customs duty and maximising the impact of advocacy within a country, it still may not be possible to achieve universal coverage for all key components of care until GDP rises substantially. Even in countries where GDP is growing at 8-10% per year, this may still take some years as in many countries the current per capita GDP is <$2,000 and HE <$100 per capita. In the interim, external assistance will often be needed if insulin, blood glucose meters and strips, and other supplies are to be provided to all children and youth in a particular country [23]. In countries where there was limited government provision, adequate human insulin and provision of two test strips per day were available in many nations for most or all children due to the dedicated actions of local diabetes associations and clinics, in partnership with international initiatives such as IDF LFAC, Changing Diabetes in Children, and Insulin for Life. Covering over 40 countries, these initiatives have the potential to make a substantial impact [23-25]. Syringes usually cost around $0.20 so the total cost of single-use syringes is substantial. Even though this is “off-label” use, syringes (and lancets) are often re-used a number of times in lower-resourced countries, apparently generally with no consequences. However, there are limits beyond which the injection becomes too painful, and risk of infection presumably increases with time. Delivery systems and insulins that are the standard in most high-income countries are costly. Pen needles and insulin cartridges are more expensive than use of syringes and vials. Use of analog insulins and insulin pump therapy is more costly again. Such interventions have advantages, but quality outcomes can be achieved without these components, and Governments should not divert limited funds to their use until all more basic components of diabetes care can be delivered. Glucagon and ketone strips help prevent serious episodes of hypoglycaemia and hyperglycaemia, and reports to LFAC indicate that fatalities from both of these conditions are

99 not uncommon in such countries. The wider introduction of urine ketone strips should be promoted as this is a relatively inexpensive supply, with glucagon also to be encouraged for families that can afford it. Further efforts in complications screening are strongly indicated as poorer blood glucose control and complications are more frequent in lower-resourced settings [5,7]. A number of lower-income countries now have pediatric endocrinologists. This is partly due to the training schools in Nairobi and Lagos established by European Society of Pediatric Endocrinology (ESPE) and International Society for Pediatric and Adolescent Diabetes (ISPAD). Only one key indicator was not correlated to GDP – the presence of at least one trained diabetes nurse educator in the country. Regional analysis indicated that nurse educators were less common in Central Asia, South America, and South-East Asia, which may reflect the more physician-centric nature of the health systems. This is in contrast to some African and Pacific nations where the number of doctors is often limited, and nurses make clinical assessments and have prescribing rights. Misdiagnosis of DKA is known in many countries, with often fatal consequences. Diabetes in young people and even adults is frequently misdiagnosed as malaria, gastroenteritis, typhoid, pneumonia, malnutrition or HIV/AIDS [26,27]. Such deaths can still occur in developed nations [28]. The authors believe that misdiagnosis is likely to be the commonest cause of death for children with diabetes in less-resourced countries.

4.4 Future directions The introduction of multiple daily dose regimens would be a useful intervention in many countries, as a number are still using twice-daily injections of pre-mixed or of individual mixtures of short- and long-acting insulin. We note that blood glucose monitoring, health professional training, and education of young patients and their families must be in place for this changeover to occur – otherwise harm could result from an increased risk of severe hypoglycaemia. Some pharmaceutical companies do offer preferential insulin pricing to low income countries, and development of regional pooled procurement programs may result in lower prices (as occurred with inhaled corticosteroids for asthma through the Asthma Drug Facility) [29,30]. An increase in the number of insulin and blood glucose monitoring manufacturers may also lead to reduced prices. Given the frequent lack of home refrigeration, studies on the efficacy of alternate methods of cooling (such as evaporative cooling using a clay pot) would be valuable, as would more detailed information on the stability of newer insulins at prolonged higher temperatures. Education campaigns are needed to address deaths from misdiagnosis and late diagnosis of DKA. Such programs have been shown to reduce the incidence of DKA [31,32], and IDF LFAC and ISPAD are promoting and facilitating use of a six-icon poster (showing the six commonest presenting features of type 1) in appropriate languages [33]. Registers, incidence and prevalence data, and epidemiology studies aid clinical management, teaching, resource allocation, and advocacy, and should be encouraged and fostered. Establishment of a mentoring/teaching relationship between a lower-resourced centre and a developed country centre with more advanced care can help with health professional training and establishment of diabetes camps.

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In conclusion, the LFAC Index of Diabetes Care for Children and Youth provides a straightforward method of assessing critical components of diabetes care globally. The results highlight gaps on a country level, and reveal regional and global patterns, thus guiding local and international interventions, and assisting advocacy. The Index could also be used to show rates of improvements over time, and assist in monitoring of interventions.

Appendix 1 - Questions in survey instrument (multiple choice answer options depended on question)

Section 1 - Insulin Q1: What is the insulin situation for children <15 years in your country? Q2: What is the insulin situation for youth 15-18 years in your country? Q3: What is the insulin situation for youth 18-25 years in your country? Q4: What insulin regimen is used for the majority of children and adolescents with type 1 at your centre? Q5: What insulin regimen is most commonly used for children and adolescents with type 1 at other centres in the country? Q6: What is the current situation regarding import duties and taxes on insulin in your country? Q7: How many families in your country have a refrigerator in their own home to store the insulin? Section 2 – Other supplies Q8: In your country, where do children and youth obtain insulin delivery systems (syringes/pens/pumps) from? Q9: In your country, what percentage of children, excluding any on pump therapy, use an insulin pen instead of syringes/needles? Q10: In your country, where do children <15 obtain meters and strips from? Q11: In your country, where do adolescents (15-18 year old) with diabetes obtain meters and strips from? Q12: In your country, where do 18-25 year olds with diabetes obtain meters and strips from? Q13: What is the status of HbA1c testing in your country? Q14: What percentage of children and youth in your country with type 1 has urine ketone strips at home? Q15: What percentage of children and youth in your country with type 1 has glucagon at home? Q16: Who is responsible for funding the cost of medical care and laboratory testing in your country, other than glucose and HbA1c, for children and youth with diabetes? Q17: Overall, what percentage of families of children and youth in your country with diabetes must travel considerable distances for diabetes supplies and review? Section 3 – Other health professionals Q18: What is the highest level of paediatric diabetes training in the diabetes team in your country? Q19: What is the highest level of paediatric nurse diabetes training in your country? Q20: What other health professionals are included in the diabetes team in your country? Q21: What professional endocrinology organisations exist in your country?

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Section 4 - Organisation of Care Q22: How is your centre currently structured with regards to diabetes care? Q23: What is the current situation regarding complications screening for microalbuminuria for children and youth in your centre? Q24: What is the current situation regarding eye complications screening for children and youth in your centre? Q25: What is the current situation regarding feet complications screening for children and youth in your centre? Q26: What is the estimated proportion of children and youth with diabetes in your centre receiving “standard” care (adequate insulin, self-blood glucose monitoring and HbA1c testing, and some diabetes education)? Q27: What is the estimated proportion of children and youth with diabetes in your country receiving “standard” care (adequate insulin, self-blood glucose monitoring and HbA1c testing, and some diabetes education)? Q28: Availability and use of treatment guidelines for management of diabetic ketoacidosis (guidelines may be ISPAD, IDF/ISPAD, CDiC, or locally developed) Q29: What emergency care – 24 hour telephone on-call service – is available to children and youth with diabetes and their families? Section 5 – Other factors Q30: What diabetes education materials for type 1 diabetes in children and youth are available in your country? Q31: Is there an active Diabetes Association in your country? Q32: Concerning diabetes camps in your country…. Q33: What level of knowledge do health professionals in your country (outside your centre) have regarding symptoms of diabetes and ketoacidosis in children and youth? Q34: Is there a childhood and youth diabetes data collection system in your country Q35: What level of childhood and youth diabetes epidemiology data is available in your country? Q36: In your country, what is the degree of engagement between diabetes health professionals and teachers at schools attended by the children and youth with diabetes?

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Acknowledgements This study was partly funded by the Leona M and Harry B Helmsley Charitable Trust, and Fondation de l’Orangerie. No potential conflicts of interest relevant to this article were reported. G.O. designed the study, conducted the analysis and wrote the manuscript, and is the guarantor. A.M. implemented the study and contributed to the analysis and manuscript. M.S. was involved in the study concept and design, and reviewed and edited the manuscript. The authors thank the experts who answered the survey from all the countries involved, Rachel Miller and Trevor Orchard (University of Pittsburgh) for assistance with the statistical analysis, and Mark Atkinson (University of Florida) for helpful comments on the manuscript. The paper has been presented in Abstract form at the October 2013 ISPAD meeting in Gothenburg (Pediatr Diabetes 2013:14 (Suppl 18):34) and the IDF Congress in Melbourne, December 2013. We thank all the experts who returned the questionnaire: Australia: Assoc. Prof. Bruce King, John Hunter Children’s Hospital, Newcastle. Azerbaijan: Dr. Gunduz Ahmadov Endocrine Centre, Baku. Bangladesh: Dr. Bedowra Zabeen, BIRDEM 2, Dhaka. Bermuda: Mrs. Debbie Jones, BMB Centre, Hamilton. Bolivia: Dr.Elizabeth Duarte, Vivir Con Diabetes, Cochabamba. Botswana: Dr. Joel Dipsalema, Botswana – Baylor Children’s Centre, Gaborone. Burkina Faso: Prof. Joseph Drabo, CHU Yalgado Ouedraogo, Ouagadougou. Cambodia: Dr. Kruy Lim, Sihanouk Hospital Center of HOPE, Sihanouk. Cayman Islands: Dr. S. Williams-Rodriguez, Cayman Islands Health Service Authority, Grand Cayman. Cuba: Dr. Manuel Vera Gonzalez, Institute de Naciona de Endocrinologia, Havana. Czech Republic: Dr. Z. Sumnik, University Hospital Motol, Prague. Denmark: Dr. Henrik B. Mortensen, Herlev Hospital, Copenhagen. Dominican Republic: Senor Jose Lopez, Fundacion Apprendiendo a Vivir, Santa Dominigo. Democratic Republic of Congo: Dr. Marguerite de Clerck, Kinshasa; Mr. Alfred Kasingi, ADIC, Goma.; Ecuador: Ms. Mercedes Lopez, FDJE, Guayaquil; Dr. Aracely Basurto, FUVIDA, Quito. Egypt: Prof. Mona Salem, Ain Shams University, Cairo. Eritrea: Mr. Rezene Araya, Eritrean National Diabetes Association, Asmara. Ethiopia: Ms. Misrak Tarekegn/Prof Ahmed Reja, Ethiopian Diabetes Society, Addis Ababa. Fiji: Dr. Rigamoto Taito, Lautoka Hospital, Lautoka. France: Prof. Jean-Jacques Robert, Hôpital Necker, Paris. Gambia: Dr. Alieu Gaye, Pakala Clinic, Banjul. Germany: Prof. Thomas Danne, Kinderkrankenhaus auf der Bult, Hanover. Ghana: Dr. Emmanuel Ameyaw, Komfo Anokye Teaching Hospital, Kumasi; Mrs. Elizabeth Denyoh, Ghana Diabetes Association, Accra. Guatemala: Dr. Gloria Soto, Roosevelt Hospital, Guatemala City. Guyana: Ms. Glynis Beaton, Guyana Diabetes Association, Georgetown. Haiti: Dr. Nancy Charles-Larco, FHADIMAC, Port-au- Prince. Hungary: Prof. L Madacsy, Semmelweis University, Budapest. India: Dr. Sharad Pendsey, DREAM TRUST, Nagpur; Dr. Nihal Thomas, Christian Medical College, Vellore; Dr. Banshi Saboo, DiaCare-Diabetes Care & Hormone Clinic, ; Dr. Santosh Gupta, Rama Krishna Mission Sevashram Hospital, Haridwar. Iraq: Dr. Ramadin Yousef Mohamed, Diabetic Child Association, Erbil. Ireland: Dr. Declan Cody, Our Lady’s Children’s Hospital, Crumlin, Dublin. Italy: Prof. Giovanni De Giorgi, Servizio Regionale di Diabetologia Pediatrica, Umbria. Jamaica: Mrs. Lurline Less, Diabetes Association of Jamaica, Kingston. Japan: Prof. Shin Amemiya, Saitama Medical University, Saitama City. Kenya: Ms. Atieno Jalang'o, DiabetesKenya, Nairobi. South Korea: Dr. Byung-Kuy Suh, Seoul St. Mary's Hospital, Seoul. Liberia: Dr. David Okiror, James Davis JR

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Memorial Hospital, Monrovia; Liberia. Ms. Josephine Gbayeah, Ganta United Methodist Hospital, Ganta. Luxembourg: Dr. Carine de Beaufort, Clinique Pediatrique de Luxembourg. Malaysia: Prof. M. Yazid Jalaludin, University Malaya Medical Centre, Kuala Lumpur. Maldives: Ms. Aishath Shiruhana, Diabetes Society of Maldives, Malé. Mali: Ms. S. Besançon/Prof Sidibe, Santé Diabète/Hopital du Mali, Bamako. Mauritania: M. Wane Alghassoum, Espace enfants diabetiques, Nouakchott. Mexico: Sr. Nelly Rodriguez/Dr. Oscar Flores Caloca, Asociación Mexicana de Diabetes, Nuevo León; Sr. Ana Jency Garcia, Asociación Mexicana de Diabetes, Guanajuato, León; Sr. Sara Del Carmen Pimentel Solis, Asociación Mexicana de Diabetes en el Sureste, Mérida; Sr. Maria Mota, Asociación Mexicana de Diabetes, Guadalajara, Jalisco; Dra. Elisa Nishimura Meguro, IMSS, México City; Dr Ana Lilia Rodriguez, Instituto Nacional de Perinatologia, México City. Prof. Mira Samardzic, Podgorica, Montenegro. Morocco: Prof. Amina Balafrej, BADIL, Rabat. Nepal: Dr. Buddhi Paudyal, Patan Hospital, Kathmandu. Netherlands: Dr. Henk-Jan Aanstoot, Diabeter, Rotterdam. New Zealand: Assoc. Prof. Esko Wiltshire, Wellington. Nigeria: Dr. Abiola Oduwole, Lagos University Teaching Hospital, Lagos; Dr. Jerome Elusiyan, OAUTHC, Ile-Ife. Norway: Dr. Hans-Jacob Bangstad, Oslo University Hospital, Ullevål. Pakistan: Prof. Yakoob Ahmedani, Baqai Institute of Diabetology and Endocrinology, Karachi; Dr Jamal Raza, National Institute of Child Health, Karachi. Papua New Guinea: Dr. Graham Ogle, HOPE worldwide (PNG). Philippines: Dr. Jackie Lou Soriano, University of the Philippines, Manila. Republic of Congo: Dr. Charley Elenga-Bongo, Hôpital Général Adolphe Sicé ,Pointe-Noire. Romania: Prof. Viorel Şerban, Fundaţiei Cristian Şerban, Bizias. Rwanda: M. Francois Goma, Rwandan Diabetes Association, Kigali. Singapore: Dr. Warren Lee, KK Children’s Hospital. Solomon Islands: Assoc. Prof. Bruce King, visiting expert, Honiara Hospital, Honiara. Sri Lanka: Dr Mahen Wijesuriya, Diabetes Association of Sri Lanka, Colombo. Sudan: Prof. Mohamed Ahmed Abdullah, University of Khartoum. Sweden: Dr. Ragnar Hanas, Uddevalla Hospital, Uddevalla. Tajikistan: Dr. Jamolovna, National Republican Endocrine Centre, Dushanbe. Tanzania: Dr. Edna Majaliwa, Muhimbili National Hospital, Dar-es-Salaam. Thailand: Dr. Somchit Jaruratanasirikul, Prince of Songkla University, Sonkhla; Dr. O. Panamonta, Kaen University, Khon Kaen; Dr. S. Likitmaskul, Siriraj Paediatric Centre, Bangkok. Togo: Dr. P. Tossou, ATD, Lome. Uganda: Dr Silver Bahendeka, St Rapahel Nsambya Hospital, Kampala. United Kingdom: Prof. Stephen Greene, Dundee University, Dundee. USA: Dr. Larry Deeb, Tallahassee, Florida. Uzbekistan: Prof. Ismailov, Institute of Endocrinology, Tashkent. Vietnam: Dr. Huynh Thi Vu Quynh, Children’s Hospital 2, Ho Chi Minh City. Zimbabwe: Mr. Ngoni Chigwana, Zimbabwean Diabetes Association, Harare.

References 1. International Diabetes Federation. IDF Diabetes Atlas (6th ed.) Brussels: International Diabetes Federation 2003;44-45. 2. Patterson C, Guariguata L, Dahlquist G, Soltész G, Ogle G, Silink M. Diabetes in the young – a global view and worldwide estimates of numbers of children with type 1 diabetes. Diabetes Res Clin Pract 2014;103:161-175. 3. Mortensen HB, Robertson KJ, Aanstoot HJ et al. Insulin management and metabolic control of type 1 diabetes mellitus in childhood and adolescence in 18 countries. Hvidøre Study Group on Childhood Diabetes. Diabet Med 1998;15:752-759.

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4. Cameron FJ, de Beaufort C, Aanstoot H-J et al. Lessons from the Hvidoere International Study Group on childhood diabetes: be dogmatic about outcomes and flexible about approach. Pediatr Diabetes 2013;14:473-80. 5. Majaliwa ES, Munubhi E, Ramaiya K et al. Survey on acute and chronic complications in children and adolescents with type 1 diabetes at Muhimbili National Hospital in Dar es Salaam, Tanzania. Diabetes Care 2007;30:2187-2192. 6. Mukama LJ, Moran A, Nyindo M, Philemon R, Msuya L. Improved glycemic control and acute complications among children with type 1 diabetes mellitus in Moshi, Tanzania. Pediatr Diabetes 2013;14:211-216. 7. Marshall SL, Edidin D, Sharma V, Ogle G, Arena VC, Orchard T. Current clinical status, glucose control, and complication rates of children and youth with type 1 diabetes in Rwanda. 8. International Diabetes Federation. Access to Insulin and Diabetes Supplies. In Diabetes Atlas (2nd edn.) Brussels: International Diabetes Federation 2003:193-205. 9. Beran D, Yudkin JS, de Courten M. Assessing health systems for type 1 diabetes in sub- Saharan Africa: developing a ‘Rapid Assessment Protocol for Insulin Access’. BMC Health Serv Res 2006;6:17. 10. Beran D, Yudkin JS, de Courten M. Access to care for patients with insulin-requiring diabetes in developing countries: Case studies of Mozambique and Zambia (Diabetes Care 2005;28:2136-2140. 11. Beran D, Higuchi M. Delivering diabetes care in the Philippines and Vietnam: policy and practice issues. Asia Pac J Public Health 2013;25:92-101. 12. Beran D, Abdraimova A, Akkazieva B, McKee M, Balabanova D, Yudkin JS. Diabetes in Kyrgyzstan: changes between 2002 and 2009. Int J Health Plann Manage 2013;28:e121- 137. 13. Danne T, Bangstad H-J, Deeb L et al. Insulin treatment. Pediatric Diabetes 2014;15 (Suppl 20):115-134. 14. Rewers MJ, Pillay K, de Beaufort C et al. Assessment and monitoring of glycemic control. Pediatric Diabetes 2014;15 (Suppl 20):102-114. 15. Lange K, Swift P, Pankowska E, Danne T. Diabetes education. Pediatric Diabetes 2014; 15 (Suppl 20);77-85. 16. Donaghue KC, Wadwa RP, Dimeglio LA et al. Microvascular and macrovascular complications. Pediatric Diabetes 2014;15 (Suppl 20): 257-269. 17. World Bank Open Data. Available from https://www.data.worldbank.org. Accessed 4 March 2014. 18. Central Intelligence Agency – The World Factbook. Available from https://www.cia.gov/library/publications/the-world-factbook/. Accessed 7 April 2013. 19. International Energy Agency. World Energy Outlook – Access to Electricity. Available from http://www.iea.org/publications/worldenergyoutlook/resources/energydevelopment/ accesstoelectricity/. Accessed 4 March 2013.

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20. World Health Organisation. WHO Model lists of essential medicines. Available from http://www.who.int/medicines/publications/essentialmedicines/en/. Accessed 4 Mar 2014. 21. Brange J. Stability of insulin: Studies on the physical and chemical stability of insulin in pharmaceutical formulation, Boston: Kluwer Academic Publishers, 1994. 22. Health Action International 2010. A one-day snapshot of the price of insulin across 60 countries. Available from http://www.haiweb.org/medicineprices/07072010/Global_briefing_note_FINAL.pdf. Accessed 14 August 2014. 23. Atkinson M, Ogle GD. Improving diabetes care in less-resourced countries – challenges and opportunities Lancet Diabetes and Endocrinology 2013:1:268-270. 24. Paudyal B, Ogle G, Shrestha S, Allen H. Treating type 1 diabetes in Nepal: experience from Patan Hospital and the International Diabetes Federation Life for a Child program. Pediatr Diabetes 2012;13(Suppl 17):136. 25. Marshall SL, Edidin DV, Arena VC et al. Glucose control in Rwandan youth with type 1 diabetes following establishment of systematic HbA1c based, care and education. Diabetes Res Clin Pract 2015;107:113-122. 26. Rwiza HT, Swai ABM, McLarty DG. Failure to diagnose ketoacidosis in Tanzania. Diabet Med 1986;3:181-183. 27. Makani J, Matuja W, Liyombo E, Snow RW, Marsh K, Warrell DA. Admission diagnosis of cerebral malaria in adults in an endemic area of Tanzania: implications and clinical description. QJM 2003;96:355–62. 28. Ali Z, Levine B, Ripple M, Fowler DR. Diabetic ketoacidosis – a silent death. Am J Forensic Pathol 2012;33:189-193. 29. Beran D, Basey M, Wirtz V, Kaplan W, Atkinson M, Yudkin JS. On the road to the insulin centenary. Lancet 2012;380:1648. 30. Ait-Khaled N, Enarson DA, Bissell K, Billo NE. Access to inhaled corticosteroids is key to improving quality of care for asthma in developing countries. Allergy 2007;62:230-236. 31. Vanelli M, Chiari G, Ghizzoni L et al. Effectiveness of a prevention program for diabetic ketoacidosis in children. An 8 year study in schools and private practices. Diabetes Care 1999:22:7-9 32. King BR, Howard NJ, Verge CF et al. A diabetes awareness campaign prevents diabetic ketoacidosis in children at their initial presentation with type 1 diabetes. Pediatric Diabetes 2012:13:647-651 33. International Diabetes Federation Life for a Child Program DKA awareness program. Available at http://www.idf.org/lifeforachild/education-resources/dka-awareness. Accessed 5 March 2014.

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8.7 Paper 7

Klatman EL, McKee M, Ogle GD. Documenting and visualising progress towards universal health coverage for people with type 1 diabetes. Diabetes Research and Clinical Practice 2019;157:107859.

Authors: 1 Emma Louise Klatman email: [email protected] 2 Martin McKee email: [email protected] 1, 3 Graham David Ogle email: [email protected] 1 Life for a Child Program, Glebe, Sydney, Australia 2 Department of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, United Kingdom 3 Diabetes NSW & ACT, Glebe, Sydney, Australia Corresponding author – Emma Klatman, [email protected] Tel +44 7478 731550

Correspondence to: Emma Louise Klatman, Life for a Child Program, GPO Box 9824, Sydney NSW 2001, Australia

Author’s contributions: ELK compiled the data, conducted the analysis, and wrote the first draft of the paper. MM conceived the self-sustainability assessment and substantially contributed to the manuscript. GDO conceived the study and co-wrote the manuscript.

Word count: Abstract 250, Main body 3,587

Tables: 2 Figures: 3

Disclosures Statement: Emma Louise Klatman and Graham David Ogle report a grant from The Leona M. and Harry B. Helmsley Charitable Trust during the conduct of the study. The Trust did not have any input into the writing of the paper or the decision to submit it for publication. Martin McKee has no disclosure statements.

Funding: The salary of Emma Louise Klatman was fully covered and the salary of Graham David Ogle was partly covered by a grant from the Leona M. and Harry B. Helmsley Charitable Trust. Aside from the funding, the Trust did not have any role in the writing of the manuscript or the decision to submit it for publication.

Acknowledgements: We thank all country respondents for their time and effort in answering the questionnaire and also helping with follow-up questions. We also thank the World Health Organization for usage of published materials.

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Abstract Aims Global governments have committed to achieve Universal Health Coverage (UHC), ensuring access to quality and affordable healthcare for all. This is fundamental for those with type 1 diabetes mellitus, who require daily access to both insulin and blood glucose test strips to survive. This group risks being left behind by global initiatives that fail to consider these particular needs. Methods A questionnaire was distributed to key informants in 37 less-resourced countries. Seven high- income countries were also included for comparison. We drew on a WHO framework developed to assess progress towards UHC to create scales on three dimensions: population covered, services provided and direct costs. A fourth dimension, availability, was added. Results were grouped into six patterns and visually displayed with radar graphs. Results 65% of the less-resourced national health systems provided insulin, with medians of 67% for service provision (equating to Human Regular and NPH), 55% direct costs covered, and 75% availability. Test strips were only provided in 14% of the less-resourced systems, with medians 42% (less than two strips per day), 76%, and 88% respectively. Six patterns of provision were identified. Progress correlated with income level, yet some low-income countries are achieving provision for insulin and test strips for those enrolled in health insurance schemes. Conclusion No less-resourced country had even near-complete coverage for insulin, and coverage was worse for test strips. This study demonstrates the utility of this framework which could be developed as a means of tracking progress in meeting the needs of people with diabetes. Keywords: Universal Health Coverage, Sustainable Development Goals, Diabetes, Type 1 Diabetes, Insulin, Blood Glucose Monitoring

1. Background People with type 1 diabetes mellitus (T1DM) face severe risks if they cannot access insulin and test strips. Although their situations have improved greatly in some countries [1], many still face the prospect of premature death and severe complications because of an inability to secure reliable and affordable supplies of these products.[2–8] Fortunately, health is now high on the global agenda, with Goal 3 of the United Nations’ Sustainable Development Goals calling on governments to ensure healthy lives and promote wellbeing for all at all ages[9] by meeting targets including Target 3.4, “reduce by one-third premature mortality from non-communicable diseases through prevention and treatment…”[9]; and Target 3.8, “achieve universal health coverage (UHC), including financial risk protection, access to quality essential health-care services, and access to safe, effective, quality, and affordable essential medicines and vaccines for all”[9]. These commitments have stimulated numerous initiatives to develop and strengthen health financing and delivery systems but there is a risk that the very specific needs of the estimated 425 million people worldwide who have diabetes, 80% of whom live in low-and

108 middle-income countries, could be overlooked[10]. Providing diabetes care has many challenges, including for instance procuring, storing, and distributing a product such as insulin that requires a complex management system, including a cold chain. It has been previously shown that access to crucial medical supplies for people with diabetes varies globally.[1,8,11– 13] Coverage by health services has several dimensions. This is commonly represented by means of a cube (Figure 1),[14,15] with three dimensions: population covered, services or treatments covered, and share of the direct cost covered by the health system.

Figure 1: The three dimensions of universal health coverage.

Source: The World Health Organization, permission to reproduce material granted 12th March, 2018.

2. Methods A self-assessment questionnaire on sustainability, distributed to diabetes centres supported by the International Diabetes Federation Life for a Child Program (LFAC) in 2016-17, was the primary source of data. The instrument included a range of questions on aspects of national health systems, and government supply of insulin and test strips, and their costs and availabilities in national health systems, private and public retail pharmacies, and health insurance schemes. Before distribution it was reviewed by experts in diabetes access in less- resourced countries, and was distributed in English, French and Spanish. The self-assessment was completed by the senior person in the organization supported by LFAC that provided clinical care to young people with diabetes in that country. The self- assessment was distributed to 37 countries: Azerbaijan, Bangladesh, Bolivia, Burkina Faso, Burundi, Cambodia, Central African Republic, Democratic Republic of Congo, Dominican Republic, Ecuador, Eritrea, Ethiopia, Ghana, Guatemala, Guyana, Haiti, Jamaica, Kenya, Liberia, Maldives, Mali, Mauritania, Mexico, Nepal, Nigeria, Pakistan, Philippines, Republic of Congo, Rwanda, Sri Lanka, Sudan, Tajikistan, Tanzania, Togo, Uganda, Uzbekistan, and Vietnam. Questions included end-user costs of 10mL of insulin (analogue or human long/short acting or pre-mixed insulin as applicable) and blood glucose testing strips. Costs were obtained in local

109 currency and then converted to US$ at the time. When prices were reported as a range, the lowest value was used for analysis. When necessary, follow up questions were clarified. Information on coverage, provision, costs, and availability was also collected from senior diabetes figures in Australia, France, Italy, Japan, New Zealand, Sweden, and the United Kingdom. Provision of services was defined as insulin and strips being supplied through the public health system. Each dimension was defined as a percentage as follows: Population was defined as the percentage of the population who can potentially access the public health service. When health system coverage was not universal, figures were corroborated by published sources where possible. Many countries have a variety of health systems, including private insurance schemes used predominantly by the wealthy or have services exclusively accessed by certain groups such as armed forces. In this study, we reviewed those government health systems in which a substantial proportion of the population was enrolled. For instance, two in particular had several systems that each covered a substantial share of the population, with differing eligibility and entitlements. Mexico has three large systems: IMSS for private sector employees and dependents (enrolment 58.9% of the population), ISSSTE – for public sector employees and dependents (10.6%) and the basic national health system Seguro Popular for those not covered by IMSS or ISSTE (44.9%) ( There is some overlap in enrolment between the systems). [16]. In Tanzania, the National Health Insurance Fund (NHIF) is mandatory for public servants and their dependents[17] and is also available for other workers if they can afford membership fees. Enrolment was noted to be 7.2% in 2014[18], with the Tanzanian in-country investigator reporting a rise in this figure to 27% in 2017. The remainder of the population have access to the basic national public health system. For Services, two empirical scales were developed: for insulin, we used a four point scale, which we expressed as a percentage, with the provision of analogue insulin scaled 100%, NPH and regular 67%, pre-mixed only 33.3%, and none 0%; for test strips, provision was expressed on a five point scale as 100% for four or more test strips/day, 75% for three/day etc., with 0% for no provision. Direct cost was calculated as the out of pocket cost people with diabetes pay for services in the public health system divided by the costs of those same services when purchased completely out of pocket (retail cost at a private pharmacy). Availability was estimated by the country correspondent from a scale of 100% being always available, 75% mostly available, 50% sometimes available, 25% rarely available, and 0% never available. 2016 Gross National Income per capita, atlas method (current US$)[19] and World Bank country income level classifications were used.[19] Radar graphs were developed in Microsoft Excel to provide a visual representation of provision for insulin and test strips in each country. Provision was represented by shading within an equilateral triangle (Figure 2.) The three WHO UHC dimensions were each represented by distance from the middle of the triangle to the respective point of the triangle, and the area included was shaded. Then availability, as the fourth dimension, was designated by a particular colour of a traffic light

110 system. Green shading indicates 100% availability, light green 75-100%, amber 50-75%, light red 25-50%, and dark red 0-<25%.

Figure 2: Country radar graphs of the six patterns of provision for insulin and test strips

3. Results 37 countries returned the self-assessment by January 2018. The geographic distribution was Africa (18 countries), Americas (8), Asia (7), Caucasus/Central Asia (3), and Western Pacific (1).

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Respondents included: one mission hospital with the largest type 1 diabetes clinic in the country (Liberia), two Ministry of Health contacts (Burundi and Guyana), four senior endocrinologists (Azerbaijan, Ghana, Pakistan, and Philippines), five diabetes nongovernmental organisations doing extensive work in diabetes care (Burkina Faso, Democratic Republic of Congo, Dominican Republic, Guatemala, and Mali), six government hospitals (Kenya, Nepal, Nigeria, Sudan, Tajikistan, and Vietnam), and 19 national diabetes association chiefs (Bangladesh, Bolivia, Cambodia, Central African Republic, Ecuador, Eritrea, Ethiopia, Haiti, Jamaica, Maldives, Mauritania, Mexico, Republic of Congo, Rwanda, Sri Lanka, Tanzania, Togo, Uganda, and Uzbekistan). The self-assessment questionnaire was also completed by diabetes experts in seven High- income countries (HICs) in Australia, France, Italy, Japan, New Zealand, Sweden, and the United Kingdom.

3.1 Population coverage in Public Health Systems All of the less-resourced countries had some form of national public health system. However, due to geographic distance or civil disturbance (e.g. Mali), incomplete enrolment in health insurance programs (e.g. Mutuelle de Santé in Rwanda, National Health Insurance Fund in Tanzania and National Health Insurance Schemes in Ghana and Kenya), use of private health care (e.g. Ecuador), and other reasons, the coverage in the public health sector was less than 100% in some countries. 3.2 Services, Cost and Availability 3.2.1 Insulin In the 37 less-resourced countries, 24 (65%) of the profiled health systems provided insulin, with medians of 67% service provision and 55% direct costs covered, and 13 (35%) did not. Human pre-mixed insulin only was provided in two countries and NPH and regular in 20 countries. Two provided analogue insulin (10 mL 100 IU equivalent) at a modest cost (Azerbaijan [$25.00 USD] and Vietnam [$12.18 USD]). For the 24 countries that provided insulin, eight covered 100% of the costs, nine part of the costs, and seven none of the costs (Table 1). Availability ranged from 25% in Sri Lanka to 100% in Burundi, Mexico, and Tajikistan (median 75%). Although Mexico’s basic health system, Seguro Popular, only provided pre-mixed insulin, the other Mexican health systems IMSS and ISSSTE provided NPH insulin to members. The basic public health system in Tanzania provided insulin with a 64% subsidy and the NHIF provided NPH insulin free of charge.

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Table 1: Details by country for progress towards UHC for insulin and test strips in type 1 diabetes

In the 13 countries where governments did not provide insulin, out-of-pocket costs for a 10mL vial of insulin ranged from $3.84 to $34.09 (median $9.04, mean $12.55). The seven HICs all had 100% coverage through the respective national health system, with co- payments being required in two countries. Table 1 reports further details. 3.2.2 Test strips Only five (14%) of the 37 less-resourced countries provided blood glucose testing strips in their basic health systems, with medians of 42% service provision, 76% costs covered, and 88% availability. These included Guyana, Dominican Republic, Jamaica, Azerbaijan, and Tanzania. All, however, had limits on the quantities prescribed and entitlements varied. In Guyana, only young people with T1DM were eligible to receive strips, to a maximum of 50 per month at no cost, with

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90% availability. In the Dominican Republic, public hospitals in the capital provided a variable number of strips per day (up to three in some situations) at no cost with good availability. In Jamaica, test strips were moderately subsidised (56%) in the public health system, and people with diabetes were eligible to access 50 strips per month. However, availability of strips was estimated to be erratic (10% and limited to the capital city). In Azerbaijan, 50 strips per year were provided, fully subsidised, and always available. Test strips could be accessed in Tanzania’s basic public health system, where the cost was subsidised 50% and availability 75%. Tanzania’s NHIF provided 25 strips per month with full availability and no co-payment. Out-of pocket costs for one test strip ranged from $0.25 to $1.65 (median $0.49, mean $0.56). The seven HICs all had essentially 100% coverage through the respective national health system, with co-payments being required in two countries (Table 1). 3.3 Patterns We grouped countries into patterns based on population coverage, services, costs, and availability (Table 2).

Table 2: Patterns of progress towards Universal Health Coverage for insulin and test strips in type 1 diabetes

Patterns were defined as: Pattern 1: High population coverage, full provision of insulin and test strips, high proportion of direct costs covered, full availability; Pattern 2: High population coverage, full provision of insulin and test strips, high proportion of direct costs covered (with some co-payment), full availability; Pattern 3: Variable population coverage, mid- range provision of insulin with high proportion of direct costs covered, variable availability, limited provision of test strips with half or more of total direct costs covered, variable availability; Pattern 4: High population coverage, low to mid-range provision of insulin with high proportion of direct costs covered, good availability, no provision of test strips; Pattern 5:

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Variable population coverage, low to mid-range provision of insulin, with either a low proportion of direct costs covered or poor availability or both, no provision of test strips; Pattern 6: Medium to high population coverage, no provision of insulin, no provision of test strips. Azerbaijan was the only unclassifiable country as its public health system covered a large share of the population, yet a wide range of services had to be paid for at full retail costs except for 50 test strips per year. 3.3.1 Visualisation of extent of UHC Representative countries in each pattern were portrayed graphically to show differences in UHC for insulin and test strips (Figure 2). 3.4 Coverage pattern and relationship to country income Figure 3 aggregates the coverage patterns of the 36 low-resourced countries (omitting Azerbaijan) and seven HICs, by World Bank income level.[19]

Figure 3: Number of countries per pattern by World Bank classification, 2016

Data compiled from World Bank income classification [19].

3.5 Other results Erratic availability was commonly reported, especially in rural settings. Reported reasons included pharmacy stock outs, deriving from logistical problems, cumbersome regulatory procedures, and customs and taxes. Rwanda illustrates the problems for rural residents, with few rural pharmacies. When stock-outs occur, patients must travel long distances to obtain insulin from private pharmacies, with attendant travel, accommodation, and foregone work income costs. Respondents from 34 of the less-resourced countries indicated the availability of Private Health Insurance (PHI) schemes but all described very low enrolment figures. Only five, in Ecuador, Jamaica, Mali, Sudan, and Togo, provided human insulin, with costs even more

115 expensive than when accessed in the public systems, except in Mali and Togo where enrolees pay a percentage of the indicative public system cost. Blood glucose test strips were not provided in any PHIs. Respondents from Azerbaijan and Nepal reported that their respective governments were piloting health insurance schemes, but commented that these schemes would only cover diabetes-related hospital admissions, not insulin or any other diabetes-related consumable.

4. Discussion This paper presents a framework that can be used to document progress towards meeting the needs of people with T1DM at a time when governments are implementing UHC. We apply the framework to 37 low-resourced countries, thereby illustrating the scale and nature of variation, with comparative data from seven high-income countries. Much research on UHC focuses on financial coverage or access to a small number of specific interventions, such as immunisation or access to a skilled birth attendant. However, this provides only an extremely partial picture, and as noncommunicable diseases are increasingly prioritised in the international health agenda, it is essential to include systems that can monitor the extent to which health systems are responding to T1DM, ensuring that the necessary medicines and ancillary products are available and affordable for all. We view this paper as proof of principle, rather than a set of definitive results which, ultimately, should be obtained from empirical studies. Ideally, these would involve a combination of objective measures, such as facility surveys to check price and availability, linked to data on income to assess affordability, complemented with user surveys to identify the barriers that people face in obtaining supplies.

Key Findings Six broad patterns of provision were identified. All seven high-income countries showed Patterns 1 and 2, with the public health systems providing complete coverage and availability, with a modest co-payment in the two Pattern 2 countries (Australia and Japan). As income level declined, coverage tended to decrease (Patterns 3-6). This is consistent with published data.[13] Health systems in countries showing Patterns 3-5, many of which are low-income, supply varying degrees of insulin and test strips. This indicates that some countries have made steps towards achieving coverage of tools needed for the management of T1D. These countries provide potential examples for the 13 low and lower-middle income countries showing Pattern 6 where there was no government provision. Clearly, countries must make difficult choices when resources are constrained. A decision not to provide analogue insulin can be justified, as the benefit of the substantially more expensive analogue over a “basal-bolus” human insulin regimen is very modest.[27,28] However, access to human short- and long-acting insulin is essential for instituting a basal-bolus regimen, which is a cornerstone of modern T1DM care.[29] This regimen cannot be delivered with pre-mixed insulin, which was the only insulin provided by two public systems. While there are many problems with insulin supply, these are even greater with test strips, with only partial provision in five of the 37 less-resourced countries. This is consistent

116 with an earlier LFAC study, which found that no public health systems in 37 LMICs and LICs provided test strips.[13] Self-monitoring of blood glucose (SMBG) is an essential tool in adequate management of T1DM. Insulin dosages can be adjusted to food and exercise patterns, dangerous extremes of blood glucose levels can be avoided entirely or more easily detected[30], and long-term complications reduced due to improved glycaemic control.[8,31] The lack of test strip provision is compounded by out-of-pocket costs as the purchase of strips can outweigh the costs of daily insulin in many countries.[6] A possible contributor to this disparity is that although the WHO has a Essential Diagnostics List that details glucose testing, it is not listed for self-management, but only to diagnose and screen for diabetes, intermediate hyperglycemia and hypoglycaemia.[32] The results demonstrate that, in addition to the three dimensions of coverage, availability must also be considered – entitlement to insulin is meaningless if it is not available. Recognising the limitations of our data, based on self-report, it is noteworthy that, of the 24 less-resourced health systems that provided insulin, 75% estimated <80% availability, with particular problems reported by many countries outside urban centres. These countries have not yet reached the voluntary global target of 80% availability of affordable essential medicines required to treat major noncommunicable diseases.[33] This study focused on insulin and test strips, but comprehensive strengthening of national health systems is needed for adequate T1DM care, including skilled health professionals, diabetes education, and inpatient services. The WHO ‘building blocks of the health system’ framework is useful in this regard, showing the importance of leadership/governance, overall health system financing, the health workforce, information and research, and service delivery.[34] Some less-resourced countries have created health insurance programs, but as other authors have noted, these face several challenges: cost recovery can be difficult, flat-rate premiums result in the most vulnerable and poor being unable to access the program, and non- mandatory membership undermines revenue generation and risk-pooling.[35] A full discussion of these issues is beyond this paper, however we note three indicative examples. The NHIF in Tanzania, which provides insulin and test strips, is compulsory for employees and their families and it is also offered to other workers and youth. For government workers, yearly fees amount to 6% of an employee’s annual salary per year (split by employee and employer)[17], with 17% of the population enrolled. The Mutuelles de Santé in Rwanda has means-tested fees. 75% of the population was enrolled in 2015[36], and human insulin was subsidised, with fair availability. Enrolled patients contributed a 10% co-payment plus prescription fees. However, there was no coverage for strips. In Ghana’s NHIS, 40% of the population was enrolled in 2016 and end-users funded annual enrolment fees through social security contributions and premium payments[37], but insulin was frequently not available and strips were not covered. In theory, private health insurance programs could potentially help people with T1DM who could afford the premiums, if those premiums were community rather than risk-related and if other barriers to recruitment were eliminated. However, the finding that these private schemes do not appear to cover outpatient medication costs, beyond those in a few countries

117 that offer human insulin only, is of concern. The ongoing expense to someone with a chronic disease should be addressed. Finally, the radar graphs/triangles compiled in this study can readily be used to document progress being made in coverage of those with other diseases.

Study limitations This study has some obvious limitations. Firstly, the data were obtained from a single investigator in each country, and thus we were unable to compare national estimates on population, services, and costs. However, the country investigators were all experts responsible for organising care for young people with diabetes in their countries and thus were able to provide a broad assessment of national context. Their assessments were intended to cover the overall national, rather than just the region where the respondent was located, and were based on his or her self-assessment and expert judgement, and at a single point in time. Additionally, indirect costs, including transportation or absenteeism, associated with accessing insulin or test strips were not taken into consideration. Finally, this survey only includes a sample of high- income countries and it excludes the USA. It, almost uniquely among high income countries does not provide universal coverage and its prices of insulin are very much higher than in comparable countries. Hence, it is widely considered an extreme outlier in international comparisons. Moreover, given the unique complexity of the US health system, with multiple payers and delivery schemes, it would be misleading to provide summary statistics. The results of this study clearly cannot be expected to provide a definitive and comprehensive assessment of patterns of price and availability. However, we hope that the framework we propose could become the basis of a system to monitor progress in the ability to manage diabetes, and thereby contribute to UHC. The next steps should include development of an agreed methodology, such as that used in the WHO/Health Action International Project on Medicine Prices and Availability,[38] that could be applied regularly in a range of countries to provide empirical, accurate, and representative data to monitor progress. This should also include measures that capture the actual financial burden falling on people living with diabetes related to their income, also including the coping strategies that they and their family members engage in[39], and recognising the barriers they often face in obtaining employment. In this respect, and while not claiming the same ambition, we note how the 2000 World Health Report[40], on assessing health systems performance, also suffered from many data gaps but stimulated a major effort that has led to a vast improvement of the available information worldwide.

5. Conclusion There is great variation in health system coverage of insulin and test strips in less-resourced countries. Provision is inadequate in all countries studied, and the situation is worse for test strips than for insulin. Until there is a system in place to monitor and ensure that both insulin and test strips are both provided to all who need them, by equitable health systems at affordable prices, Goal 3 of the Sustainable Development Goals cannot be realised for people with T1DM in less-resourced countries.

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Clinical Practice Consensus Guidelines 2018: Insulin treatment in children and adolescents with diabetes. Pediatr Diabetes 2018;19:205–26. doi:10.1111/pedi.12755. [30] Rewers MJ, Pillay K, de Beaufort C, Craig ME, Hanas R, Acerini CL, et al. Assessment and monitoring of glycemic control in children and adolescents with diabetes. Pediatr Diabetes 2014;15:102–14. doi:10.1111/pedi.12190. [31] Miller KM, Beck RW, Bergenstal RM, Goland RS, Haller MJ, McGill JB, et al. Evidence of a strong association between frequency of self-monitoring of blood glucose and hemoglobin A1c levels in T1D Exchange clinic registry participants. Diabetes Care 2013;36:2009–14. doi:10.2337/dc12-1770. [32] World Health Organization. Second WHO Model List of Essential In Vitro Diagnostics Second WHO Model List of Essential In Vitro Diagnostics 2019. https://www.who.int/medical_devices/publications/Standalone_document_v8.pdf?ua =1 (accessed July 9, 2019). [33] World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013-2020 2013. http://apps.who.int/iris/bitstream/10665/94384/1/9789241506236_eng.pdf?ua=1 (accessed April 3, 2018). [34] World Health Organization. Monitoring the building blocks of health systems: a handbook of indicators and their measurement strategies 2010. http://www.who.int/healthinfo/systems/monitoring/en/ (accessed February 9, 2018). [35] Averill C, Marriott A. Universal Health Coverage Why health insurance schemes are leaving the poor behind. 2013. [36] USAID. Health Insurance Profile: Rwanda 2016. http://www.africanstrategies4health.org/uploads/1/3/5/3/13538666/country_profile_- _rwanda_-_us_letter.pdf (accessed February 8, 2018). [37] Alhassan RK, Nketiah-Amponsah E, Arhinful DK. A review of the national health insurance scheme in Ghana: What are the sustainability threats and prospects? PLoS One 2016;11:1–16. doi:10.1371/journal.pone.0165151. [38] World Health Organization and Health Action International. Measuring medicine prices, availability, affordability and price components. Switzerland: 2008. [39] Murphy A, Hanson K, Mcgowan C, Mckee M, Suhrcke M. Coping with healthcare costs for chronic illness in low-income and middle- income countries: a systematic literature review. BMJ Glob Heal 2019;4:1–8. doi:10.1136/bmjgh-2019-001475. [40] World Health Organization. The World health report 2000 : health systems : improving performance 2000. http://www.who.int/whr/2000/en/whr00_en.pdf?ua=1 (accessed July 17, 2018).

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8.8 Paper 8

Ogle GD, Kim H, Middlehurst AC, Silink M, Jenkins AJ. Financial costs for families of children with Type 1 diabetes in lower-income countries. Diabetic Medicine. 2016;33:820-826.

Authors: 1,2G.D. Ogle, FRACP 3H. Kim, BPharm 1,2A.C. Middlehurst, CDE 1,4Martin Silink, MD 1,3,5A.J. Jenkins, MD

Institutions: 1International Diabetes Federation Life for a Child Program, Glebe, Sydney, Australia 2Diabetes NSW, Glebe, Sydney, Australia 3NHMRC Clinical Trials Centre, University of Sydney, Sydney, Australia 4Children’s Hospital at Westmead, Sydney, Australia 5Insulin for Life Australia and Global, Caulfield, Melbourne, Australia

Corresponding author: Dr. Graham Ogle, [email protected]

Word count: Abstract 244, Main body 2,876 Tables: 2 Figures: 2

Funding sources: Hannah Kim was funded by a Summer Student Research Grant from the University of Sydney and NHMRC Clinical Trials Centre. This research was part-funded by the Leona M. and Harry B. Helmsley Charitable Trust.

Bulleted novelty statement • There is little published information on the comparative costs of care for a child with Type 1 diabetes in less-resourced countries, or the proportion of family income spent on such care. • The study highlights the high proportional cost of self-monitoring of blood glucose. • The study suggests insulin and meter/strip prices are decreasing in some countries, but remain prohibitively high for many families. • Awareness of costs of care may promote review of national and international diabetes care policies and support programs, and dialogue with and action by other key stakeholders, such as industry.

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Abstract Aims. Assess direct costs of necessary consumables for minimal care of a child with Type 1 diabetes in countries where the public health system does not regularly provide such care. Methods. Supply costs were collected January 2013 to February 2015 from questionnaires submitted by centres requesting International Diabetes Federation Life for a Child Program support. All 20 centres in 15 countries agreed to use of their responses. Annual costs for minimal care were estimated as: 18x10mL 100 I.U./ml insulin, 1/3 cost of a blood glucose meter, two blood glucose test strips/day, two syringes/week, and four HbA1c tests/year. Costs were expressed in USD, and as % of Gross National Income (GNI) (Purchasing Power Parity) per capita. Results. Minimum (range (median)) supply costs through the private system were: insulin 10 mL 100 I.U./mL equivalent vial: $5.10-$25 ($8.00), blood glucose meter: $15-$121 ($33.33); test strip: $0.15-$1.20 ($0.50); syringe: $0.10-$0.56 ($0.20); HbA1c: $4.90-$20 ($9.75). Annual costs ranged $255 (Pakistan) to $1,185 (Burkina Faso), with a median of $553. Annual %GNI costs were 12-370% (median 56%). For the lowest 20% income earners the annual cost ranged 20- 1,535% (median 153%). St. Lucia and Mongolia were the only countries whose governments consistently provided insulin. No government provided meters and strips, which were the most expensive supplies (62% of total cost). Conclusions. In less-resourced countries, even minimal care is beyond many families’ means. In addition, families face additional costs such as consultations, travel and indirect costs. Action to prevent diabetes-related death and morbidity is needed.

Introduction Type 1 diabetes mellitus (Type 1), the commonest childhood endocrine disorder, is fatal without exogenous insulin therapy and careful treatment. There are ≈491,000 children <15 years of age with diabetes[1], of which 34% live in low- and lower-middle income countries, as defined by the World Bank[2]. Higher-income countries generally have universal health-care, regularly reviewed treatment guidelines, and active diabetes associations and professional bodies advocating for diabetes care. Governments in these countries usually provide diabetes supplies free or at a more affordable subsidised price. However, this is not the case in many lower-income countries with under-resourced medical systems. In such countries Type 1 management poses a major financial burden on the healthcare system and on the individual and/or their family, which can lead to fragmentary and compromised health-care and treatment adherence, extremes of glycaemia, the early development of chronic complications, and premature death[3-10]. The lowest acceptable level of care in very limited resource health-care settings – “minimal care” – is defined as access to adequate insulin, diabetes education, monitoring and medical care[11]. Diabetes aid organisations, such as the International Diabetes Federation (IDF) Life for a Child program (LFAC), exist to at least partially support a subset of the world’s poorest children and youth with Type 1[12]. Prior papers have reported the estimated direct care costs of Type 2 diabetes (T2D) in various lower-income countries[13,14]. There are also a handful of studies in individual countries on actual expenditures by families with a child or adult with Type 1 [3,4,15,16].

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This study assesses the direct costs to the family of consumables needed for the minimal care of a child with Type 1 diabetes in 15 countries where the public health system does not provide such care, and relates these costs to a typical local income.

Methods Local supply costs were collected from questionnaires submitted during January 2013 to February 2015 by medical centres requesting LFAC support. LFAC has a standardised questionnaire (in English, French and Spanish), that is sent to all new centres requesting support, and includes questions about the current cost of diabetes supplies if they cannot be obtained from the government healthcare system. The questionnaire also asked the percentage of families with a person aged <23 years with Type 1 who needed assistance beyond their family resources to cover the cost of each ‘minimum care’ supply. Cost questions included: a 10mL vial of insulin (100 I.U./mL equivalent), a blood glucose meter, a blood glucose test strip, an insulin syringe, and a HbA1c test. Data were converted to USD equivalent at the time. When prices were expressed as a range in a particular country, the lowest price was used for analysis. For the six centres in India, results are expressed as a median (range), with the median used in the country analysis. The total annual supply cost for a person with Type 1 was estimated as provision of 18 vials of insulin (assuming daily usage of 40-45 I.U. with a little wastage, based on LFAC clinical experience), one blood glucose meter every three years, two blood glucose test strips per day, two insulin syringes per week (i.e. implying some reuse), and four HbA1c tests per year. The following economic data were obtained from the World Bank database[2]: Gross National Income (Purchasing Power Parity (PPP)) per capita, health expenditure per capita, and the mean income per year of the lowest 20% of the population. Data were managed in Excel and descriptive statistics performed.

Results Twenty filled questionnaires were received from 15 countries: Benin, Burkina Faso, Cambodia, Central African Republic, Ecuador, India (six centres), Ivory Coast, Malawi, Mauritania, Mongolia, Nepal, Democratic People’s Republic of Korea (DPR Korea, (North Korea)), Pakistan, St Lucia, and Somalia. Responders were: nine Diabetes Associations, three Ministry of Health / government hospitals (Nepal, DPR Korea, St. Lucia), six private clinics/foundations (Bangalore, Indore, Belgaum, Kota, Pune, Visakhapatnam), one mission hospital (Pakistan), and one private university hospital (Somalia). Across all countries, the median % of families needing supply support were: 88% for insulin, 90% for blood glucose test strips, 84% for syringes and 90% for HbA1c. Correspondence by LFAC with the participating clinics determined that the government consistently provided insulin either free or at a minimal cost in only St. Lucia and Mongolia. In all others, families must buy insulin at market rates some or all the time, except if supplies are available through charitable organisations.

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Aside from free government provision of HbA1c tests in Mongolia and of syringes in St. Lucia, non-insulin diabetes supplies in all countries (meters, strips, syringes, and HbA1c tests) must be purchased most or all of the time, except if provided by charitable organisations. The estimated costs to a family for diabetes consumables for a child or adolescent with Type 1 in the 15 countries studied, including the mean of the six centres in India, are summarised in Table 1. For countries that consistently provided supplies at no cost, e.g. insulin in St. Lucia and Mongolia, the cost to the family was listed as $0. If HbA1c testing was not available (DPR Korea and Somalia) this cost was also recorded as $0. The costs at each of the six independent clinics in India varied little between centres (Table 2).

Table 1: Costs in all countries Insulin cost % income Annual (100 IU/mL Blood Blood Annual spent on cost of Country 10mL glucose glucose Syringe HbA1c costs as a direct costs direct equivalent meter strip % HE pc by lowest supplies vial) 20% Benin $8.00 $37.50 $0.50 $0.27 $9.50 $588 1,782% 248%

Burkina Faso $10.00 $30 $1.20 $0.19 $20.00 $1,185 3,118% 505%

Cambodia $10.00 $40.00 $0.30 $0.50 $10.00 $504 988% 117% Central African $18.62 $121.46 $0.39 $0.56 $4.90 $737 4,094% 1,535% Republic Ecuador $6.10 $45.00 $0.72 $0.30 $9.00 $718 199% 62% India $5.75 $19.40 $0.23 $0.12 $6.60 $314 536% 46% (median) Ivory Coast $5.10 $43.20 $0.48 $0.26 $17.40 $553 628% 153% Malawi $25.00 $25.00 $0.56 $0.50 $20.00 $999 3,996% 1,480% not not not Korea, DPR $10 $100.00 $0.90 $0.20 available $891 available available Mauritania $7.79 $50.78 $0.54 $0.20 $14.22 $630 1,212% 198% Mongolia $- $52.00 $0.60 $0.18 $- $474 204% 36% Nepal $7.50 $25.00 $0.50 $0.10 $8.13 $551 1,531% 189% Pakistan $4.98 $30.08 $0.15 $0.15 $7.52 $255 654% 38% St Lucia $- $15.00 $0.36 $- $20.00 $348 63% 20% not not Somalia $10.00 $30.00 $0.20 $0.20 $357 2,099% available available Median $8.00 $37.50 $0.50 $0.20 $9.75 $552 988% 153%

Costs in USD. Insulin provided free in Mongolia and St. Lucia, Syringes provided free in St. Lucia, and HbA1c tests in Mongolia. HbA1c tests are not available in Somalia and DPR Korea. Some economic data are not available for DPR Korea and Somalia.

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Table 2: Costs (in USD) reported by six independent centres in India

Centre 1 Centre 2 Centre 3 Centre 4 Centre 5 Centre 6 Median

Insulin cost per 10 mL 100 IU/mL $6.70 $6.00 $5.50 $4.43 $5.18 $6.13 $5.75 equivalent vial % needing insulin 75% 30% 71% 60% 100% 50% 65% support Blood glucose $19.40 $19.40 $19.20 $10.50 $21.30 $20.64 $19.40 meter

Blood glucose strip $0.39 $0.16 $0.27 $0.16 $0.18 $0.32 $0.23

% needing strips 75% 90% 71% 60% 100% 50% 73% support Syringe cost $0.11 $0.12 $0.15 $0.16 $0.10 $0.11 $0.12

% needing syringe 75% 90% 71% 60% 100% 90% 90% support

HbA1c cost $6.50 $9.70 $6.70 $2.80 $3.85 $9.60 $6.60

% needing HbA1c 75% 90% 71% 70% 100% 85% 73% support

Cost of individual diabetes supplies As shown in Table 1, across the 15 countries, diabetes consumable costs varied widely; 5-fold for insulin, 8-fold for a blood glucose meter; 8-fold for a blood glucose test strip; 6-fold for an insulin syringe and 4-fold for a HbA1c test.

Annual cost of minimum care diabetes supplies The estimated total annual cost of ‘minimum care’ diabetes supplies to the family of a child with Type 1, assuming no government or charity provision, varied 4-fold (Table 1). Figure 1 shows the total annual cost to the family of diabetes consumables expressed as a percentage of the country’s average GNI (PPP). The mean and median costs of diabetes consumables for one child or youth with Type 1 were 88% and 53% of the mean individual income, with a range of 12-370%. Costs related to mean Health Expenditure per capita are presented in Table 1.

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Figure 1: Annual Type 1 consumables costs as a % of per capita Gross National Income

Data not available for DPR Korea and Somalia

As people requiring LFAC support more frequently come from the less affluent levels of society, the costs of diabetes supplies relative to the mean annual income of the lowest 20% income earners in each country are represented in Table 1. The mean and median costs of diabetes consumables equate to 356% and 153% (respectively) of the mean individual income for the lowest 20% income, with a range of 20-1,535%.

Proportional costs of specific diabetes supplies The proportional costs of specific supplies are shown in Table 1. Test strips were generally the most expensive diabetes consumable (mean 61.9% overall), with insulin 25.9%, syringes 4.6% and HbA1c 7.7% (Figure 2).

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Figure 2: Proportional cost of each supply, by country.

Note – there was free provision of some supplies in some countries: of insulin (Mongolia and St. Lucia), syringes (St. Lucia), and HbA1c (Mongolia). HbA1c was not available in DPR Korea and Somalia.

Discussion In 15 lesser resourced countries the potential direct costs for the minimum care of a child with Type 1 diabetes varies four-fold, with a median cost of 56% of the mean annual income of an individual in that country, or 153% of the annual income of an individual in the lowest 20% income group. These high costs are beyond the means of many families in these and similar less- resourced countries, and likely contribute to the unacceptably high morbidity and premature mortality rates, and the low observed prevalence of Type 1 in such countries[10,15,17-19].

High diabetes supply costs in many less resourced countries The high diabetes care costs we have identified are in keeping with earlier studies, which mainly relate to T2D. The IDF and also the International Insulin Foundation (IIF) have assessed annual costs of care for an insulin-requiring adult with T2D. The 2006 IDF Survey[13] assumed one vial insulin (33 I.U. of 100 I.U. / ml per day), six syringes, and one blood glucose test strip per month. In Pakistan the annual cost was 14% of per capita GDP, and in 13 other low-income and lower- middle income countries (none included in our study) the mean was 28%[2006]. IIF’s assessments [14] assumed one (10 ml, 100 / I.U./ml) insulin vial per month, one syringe, one blood glucose test, one consultation and one travel cost. Total cost was $74 in Nicaragua (where the government provided free insulin), and ranged $199-427 in Mali, Mozambique, Zambia and Vietnam. In these latter countries this represented 21-75% of per capita income. Mendis et

128 al.[20] found that one month’s supply of (40 I.U.) insulin represented 19.6 days of the lowest- paid government worker in Malawi, 7.3 days in Nepal, and 4.7 days in Pakistan. Most studies of costs for families with a Type 1 child or adult have been in situations where there was with little or no self-monitoring of blood glucose (SMBG). For the countries studied herein, in India in 2002 Shobhana[3] found in a study of mainly adults, an annual cost of $310.47 was spent on insulin and syringes. Three studies in other less-resourced countries have also been published: In Tanzania (1992) the mean annual direct cost was $287 (in a clinic of adults and some children), with the insulin component of $156 approaching average annual family income[15]. There are two publications from exclusively paediatric populations: in Sudan (1995) mean annual direct cost was $283 (23% median income) with insulin accounting for 36% of this[4]; in Mexico (2008) the mean annual direct cost was $1,670, far greater than the minimum official wage of $4 per day[16]. This was the only study where there was substantial SMBG (see below).

Inconsistent supply and high costs of insulin Supplies, even of life-saving insulin, are not constant in the public health system of the countries in this study. Prices are often substantially increased by customs duties, taxes, VAT, and mark- ups in both the private and public systems[5-8,10,14-15,20]. Our questionnaire results and experience via the LFAC program indicate that insulin provision, even for children with Type 1, is unstable in all the responding countries, with the exceptions of St. Lucia and Mongolia where the public health service provides insulin free of charge. Observed insulin prices in the present study were similar or a little less than those found in 2000-2010 by the IDF[6,13] and Health Action International[7]. Prices were generally highest in African countries and lowest in India and Pakistan. This likely represents larger market size, with greater competition and availability of generics.

Insulin syringe costs Insulin must be injected in very accurate doses, particularly in children, and syringes are the least expensive means of drug delivery. Our observed wide variation in syringe costs is consistent with previous studies[10,13-14]. Availability in the public sector is often very low, meaning that families must buy them at private outlets. Syringes are sold as single-use, but by necessity are reused[14-15], and this is generally safe[21-22]. LFAC’s standard provision is only two syringes/week, but this study’s results show that even this frequency imposes a significant cost if the family needs to purchase them. Insulin pen administration is preferable for convenience and comfort (especially important in the care of children), but both pen needles and the accompanying cartridge insulin preparations are more expensive then syringes and larger insulin vials[6,7]. As with insulin, taxes on insulin syringes and pen needles are common[10,14].

Expensive blood glucose monitoring Whilst the price of blood glucose meters has generally fallen over the last decade[6,13], likely related to marketing strategies, the high costs of blood glucose test strips remain. SMBG is essential if insulin dosage changes are to be made safely and intensive insulin regimens are to be used - without SMBG excellent blood glucose control in Type 1 cannot be achieved. In

129 affluent countries SMBG at least four times a day is usually recommended in Type 1. The range and pattern of costs of glucose test strips in this present study was similar to that in past studies[6,13], with costs highest in Africa and lowest in South Asia. However the cost of even once-daily monitoring is beyond most families in lower-income countries[3-6,9-10]. In Sudan in 2005[4], 26% of the study group (n=147) had not had a blood glucose test in the last six months. In the Cost of Diabetes in India study[23], few Type 1 subjects (18.4% of 282 subjects) were having HbA1c tests, and the mean number of blood glucose tests per year for those with Type 1 was 32. In Ghana SMBG and HbA1c testing were uncommonly performed due to cost[5]. In Mexico, the mean cost for families for SMBG (done an average twice per day) was $895 (53% of the total direct cost)[16]. Even in Brazil, an upper-middle income country where care costs are covered by the Government, the expense of blood glucose monitoring (mean of 3.4 tests per day) consumed 52.8% ($697) of the total annual cost per Type 1 patient of $1,216[24]. Insulin represented 26.1% of expenses. Further analysis of the Cobas study also noted that more frequent SMBG (up to four tests per day) was associated with improved HbA1c levels [25].

Impact of costs Diabetes care costs can be devastating for families. For the poorest of families the cost of diabetes consumables for minimum care would take all of their family income, leaving nothing for food, shelter and clothing. Some have to sell assets or borrow[26]. Many have to make chilling choices under the principle of opportunity cost – such as do they cover the cost of diabetes care for the affected child, or provide education for their other children?[6,26]. To offset high costs and increase the time until more insulin needs to be purchased, insulin doses are often missed or reduced[5,8,18,26]. Our study only evaluated the costs of diabetes consumables and HbA1c testing. Families face other direct costs – lancets for blood glucose testing, medical consultations, other laboratory tests including diabetes complication screening, and travel expenses to and from clinics. Travel costs can be high, even prohibitive[8-9,14,17,26], and overnight lodging may be needed as well[26]. In Ethiopia[17], 13% of Type 1 patients travelled over 180 km to attend a clinic. In a study of five countries, travel was the most expensive component in two[14]. There are also indirect costs of diabetes care, such as lost parental income when caring for the child or travelling to clinic, and intangible costs such as opportunity cost, anxiety and depression[4,27-28]. In the absence of provision of supplies by the public health system or benevolent sources, costs to families will only rise with time – as body weight increases and puberty occurs more insulin is needed. With time, complications screening and, accelerated by poor glucose control, the development of complications themselves can be costly. Chronic complications occur earlier and more frequently in less-resourced countries, appearing in adolescents and young adults[18-19].

Potential solutions Human insulin is less costly than insulin analogs and insulin vials cost less than cartridge/pen preparations. Syringes cost less than insulin pens, and also take less time to educate users in

130 their use. It is critical that these supplies remain available in the global market[6]. It is also essential that less-resourced governments struggling to provide insulin and other key diabetes supplies for their population purchase human insulin rather than acceding to the requests of patient groups and the influence of marketing by pharma or distributors to purchase analogs[29]. Differential pricing of diabetes consumables (so that a lower price is offered to less- resourced countries) should be encouraged, with passing on of cost-savings through the supply chain to the user[7,28]. Taxes on all diabetes supplies must be removed. More manufacturers usually leads to greater competition and lower prices. Lower-cost blood glucose testing meters and strips are urgently needed – perhaps via novel measuring techniques or a product released globally. Universal health care coverage will hopefully eventually provide coverage to all, but this may be years away in some very low-income countries. In the interim, focused advocacy, careful use of available funds and external support will be needed.

Study limitations The estimated costs of diabetes consumables were determined by report from an individual, albeit being all experienced observers who were coordinating care in their respective verified centres. The centres were in most cases the main youth diabetes centre in the respective country, and in the remaining countries were generally typical situations. Prices were not confirmed with a wider pharmacy survey or other observers (with the exception of India where six clinics were involved, with consistent results). However, the costs observed were consistent with or slightly less than previously published data in less-resourced countries[6-7,13]. We acknowledge there would be variation within many countries due to differential pricing between and within public and private sectors, and for different brands of supplies. The study design precluded assessment of actual costs - we recognise that some families would episodically receive supplies from the public health service or charitable support.

Summary and Conclusions Our results show great variation in the estimated costs of diabetes consumables for the families with children with Type 1 in less-resourced countries, but demonstrate that the cost of care for a child with Type 1 is financially overburdening and likely unaffordable for many families in lower-income countries. Insulin is essential for life of people with Type 1, but it is still not readily accessible, even for children, on an uninterrupted basis in low resourced countries, almost 100 years since its discovery. In a world where an artificial pancreas is on the horizon, no child should be dying of diabetes.

Acknowledgements The authors thank the following health professionals from the centres for providing and allowing us to use their data: Jacqueline Diquemare, Unité Diabète du CHD, Benin; Prof. Drabo, Service de Médecine Interne, CHU Yalgado, Ouagadougou, Burkina Faso; Lorraine Fraser-King, Cambodian Diabetes Association Siem Reap, Cambodia; Dr. Gaspard Kouriah, Association des Diabétiques en Centrafrique, Central African Republic; Prof. Abodo Jacko, Association Obesité

131 et Diabète de Côte D’Ivoire; Ana Fernanda Sanchez Encalada, Fundación Los Fresnos, Casa de la Diabetes, Ecuador; Dr. Srikanta, Jnana Sanjeevini Medical Centre, Bangalore, India; Dr. S. Julka, Synergy Indore Endocrine Clinic, Indore, India; Dr. M.V. Jali, Kore Hospital & MRC, Belgaum, Karnataka, India; Dr. Ramchandani, Ramchandani Diabetic Clinic, Kota, India; Dr. V.Khadilkar, Nityaasha Foundation, Pune, India; Prof. Mythili, Diabetic Child Society, Visakhapatnam, India; Rev. Timothy Ntambalika, Diabetes Association of Malawi, Blantyre, Malawi; Elghassoum Hadya Wane, Association Mauritanienne de lutte contre le Diabète, Noukachott, Mauritania; Dr. Oyun Kookhor, Diabetes Council of Mongolia, Ulan Bator, Mongolia; Dr. Santosh Pokhrel, Siddhartha Children and Women’s Hospital (SCWH), AMDA, Butwal, Nepal; Ro Un Gyong, Choe Kyong Tae Endocrine Research Institute, DPR Korea; Dr. Angela Condie, Bach Christian Hospital, Pakistan, Qualandarabad, ; Dr. Andrew Okello, SI University Hospital, Somali International University, Somalia, Africa; Dr. Jacqueline Bird, Ministry Of Health–Wellness Centres, Castries, St Lucia.

The authors thank healthcare economists Drs Philip Clarke and Derek Petrie from University of Melbourne Health Economics Research Centre for advice.

References 1. Patterson C, Guariguata L, Dahlquist G, Soltesz G, Ogle G, Silink M. Diabetes in the young - a global view and worldwide estimates of numbers of children with type 1 diabetes. Diabetes Res Clin Pract 2014;103:161-75 2. World Bank. Indicators. Available at http://data.worldbank.org/indicator. Last accessed 17 February 2015. 3. Shobhana R, Rao PR, Lavanya A, Williams R, Padma C, Vijay V et al. Costs incurred by families having Type 1 diabetes in a developing country- a study from Southern India. 2002. Diabetes Research and Clinical Practice; 55: 45-48. 4. Elrayah H, Eltom M, Bedri A, Belal A, Rosling H, Ostenson C. Economic burden on families of childhood type 1 diabetes in urban Sudan. Diabetes Research and Clinical Practice 2005 (70) 159-165. 5. Kratzer J. Structural barriers to coping with type 1 diabetes mellitus in Ghana: Experiences of diabetic youth and their families. Ghana Medical Journal. June 2012; 46 (2) 39-45. 6. International Diabetes Federation. Access to Insulin and Diabetes Supplies. Diabetes Atlas Second Edition. 2002. Chapter 5: 193-205. 7. Health Action International (HAI). A one day snapshot of the price of a medicine. Available at http://www.haiweb.org/medicineprices Last accessed 31 November 2014. 8. Higuchi M. Access to diabetes care and medicines in the Philippines. Asia-Pacific Journal of Public Health 2010; 22 (3) 96-102. 9. Kesavadev J, Sadikot S, Saboo S, Shrestha D, Jawad F, Azad K et al. Challenges in Type 1 diabetes management in South East Asia: Descriptive situational assessment. Indian Journal of Endocrinology and Metabolism. September-October 2014; 18 (5) 600-7. 10. Beran D, Yudkin J, De Courten M. Access to care for patients with insulin-requiring diabetes in developing countries: Case studies of Mozambique and Zambia. Diabetes Care. September 2005: 28 (9) 2136-2140.

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11. International Diabetes Federation. Diabetes in children: organization of care. Pediatric Diabetes 2007;8(Suppl. 1):19-25. 12. Atkinson MA, Ogle GD. Improving diabetes care in resource-poor countries: challenges and opportunities. Lancet Diabetes and Endocrinology 2013:1:268-270. 13. IDF Task Force on Insulin, Test Strips and Diabetes Supplies. Report on the international diabetes supplies survey on cost and availability 2006. International Diabetes Federation. Brussels 2007. 14. Beran D. Yudkin J. Looking beyond the issue of access to insulin: what is needed for proper diabetes care in resource-poor settings. Diabetes Res Clin Pract 2010;88:217-221. 15. Chale S, Swai ABM, Mujinja PGM, McLarty DG. Must diabetes be a fatal disease in Africa? Study of costs of treatment. BMJ 1992;304:1215-1218. 16. Altamirano-Bustamante N, Islas-Ortega L, Robles-Valdés C, Garduño-Espinosa J, Morales- Cisneros G, Valderrama A et al. Economic family burden of metabolic control in children and adolescents with type 1 diabetes mellitus. J Pediatr Endocriol Metab 2008;21:1163- 1168. 17. Alemu S, Watkins VJ, Dodds W, Turowska JB, Watkins PJ. Access to diabetes treatment in northern Ethiopia. Diabet Med 1998;15:791-794. 18. Majaliwa ES, Munubhi E, Ramaiya K Mpembeni R, Sanyiwa A, Mohn A, Chiarelli F. Survey on acute and chronic complications in children and adolescents with type 1 diabetes at Muhimbili National Hospital in Dar es Salaam, Tanzania. Diabetes Care 2007;30:2187-2192 19. Marshall SL, Edidin D, Sharma V, Ogle G, Arena VC, Orchard T. Current clinical status, glucose control, and complication rates of children and youth with type 1 diabetes in Rwanda. Pediatr Diabetes 2013;14:217-226. 20. Mendis S, Fukino K, Cameron A, Laing R, Filipe Jr A, Khatib O et al. The availability and affordability of selected essential medicines for chronic diseases in six low- and middle- income countries. Bulletin of the World Health Organization. April 2007; 85 (4) 279-289. 21. Schuler G, Pelz K, Kerp L. Is the reuse of needles for insulin injection systems associated with a higher risk of cutaneous complications? Diabetes Res Clin Pract 1992;16:209-12. 22. Thomas DR, Fischer RG, Nicholas WC, Beghe C, Hatten KW, Thomas JN. Disposable insulin syringe reuse and aseptic practices in diabetic practices. J Gen Intern Med 1992;4:97-100. 23. Bjork S, Kapur A, King H, Nair J, Ramachandran A. Global policy: aspects of diabetes in India. Health Policy 2003;66:61-72 24. Cobas RA, Ferraz MB, Matheus ASM, Tannus LRM, Negrato CA, de Araujo LA et al. The cost of type 1 diabetes: a nationwide multicentre study n Brazil. Bull World Health Organ 2013;91:434-440. 25. Gomes MB, Tannus KRM, Cobas RA, Matheus ASM, Dualib P, Zucatti AT et al. Determinants of self-monitoring of blood glucose in patients with type 1 diabetes: a multi- centre study in Brazil. Diabetic Medicine 2013;30:1255-1262. 26. Metta M, Haisma H, Kessy F, Geubbels E, Hutter I, Bailey A. “It is the medicines that keep us alive”: lived experiences of diabetes medication use and continuity among adults in Southeastern Tanzania. BMC Health Services Research 2015;15:111. 27. Yesudian C, Grepstad M, Visintin E, Ferrario A. The economic burden of diabetes in India: a review of the literature. Globalization and Health 2014, 10:80.

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28. Volman B. Direct costs and availability of diabetes medicines in low-income and middle- income countries. World Health Organization, Geneva 2008, available at apps.who.int/medicinedocs/documents/s18387en/s18387en.pdf accessed 4 March 2015 29. Beran D, Yudkin JS. The double scandal of insulin. J R Coll Physicians Edinb 2013;43:194-6.

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8.9 Paper 9

Klatman EL, Jenkins AJ, Ahmedani Y, Ogle GD. Access to blood glucose meters and strips in less- resourced countries. Lancet Diabetes & Endocrinology 2019;7:150-160.

Emma Louise Klatman1 Alicia Josephine Jenkins2 Muhammad Yakoob Ahmedani3 Graham David Ogle1,2,4 Institutions: 1International Diabetes Federation Life for a Child Program, Glebe, NSW, Australia 2NHMRC Clinical Trials Centre, University of Sydney, NSW, Australia 3Baqai Institute of Diabetology and Endocrinology, Baqai Medical University, Karachi, Pakistan 4Diabetes NSW & ACT, Glebe, NSW, Australia Keywords: monitoring blood glucose; type 1 diabetes; less-resourced countries; blood glucose meters

Contribution statement

ELK prepared the literature search, produced tables and figures, analysed the IQVIA market share and prices data, collected and analysed the data on tariffs and availability, and wrote the first draft of the manuscript. AJJ made extensive edits and writing additions to the text. MYA wrote the Pakistan vignette and provided information in other areas of the manuscript. GDO conceived the work, designed approaches, determined sources, and co-wrote and revised the manuscript.

Abstract Blood glucose meters and test-strips are largely inaccessible to, and infrequently used by, people with diabetes in less-resourced countries. Furthermore, availability in health facilities is also often very limited. This is despite their need in myriad clinical settings at all levels of the health system, and the numerous research studies and international guidelines that describe the value of self-monitoring of blood glucose in diabetes care, particularly in type 1 diabetes. This is the first comprehensive review assessing global access to blood glucose meters and test-strips. The paper systematically sources past publications (2000-2017) and collates published information on cost, availability, system accuracy, competitive bidding, technological trends and non-financial barriers. New information is also provided on global market share data and prices, taxes and tariffs, and availability. The review recommends that relevant international agencies prioritise attention to this issue. Meters and strips should be viewed similarly to essential medicines to reduce tariffs and taxes. Unified global system accuracy requirements, and accountable post-marketing evaluations would also be beneficial. Preferential pricing arrangements, pooled procurement, and best-purchasing practices could aid in lowering direct costs. These supplies should also be included in national health insurance schemes. Accompanying enhanced diabetes education of

135 health professionals and patients is critical. Finally, as technology advances for those who can afford new interstitial fluid glucose monitoring systems, it is essential that blood glucose meters and strips remain available and become more affordable in less-resourced settings.

Search strategy panel The PubMed database was searched (using KU Leuven 2Bergen Biomedical Library) during November 2016-July 2017, with the terms “blood glucose monitoring” and/or “SMBG” in conjunction with “type 1 diabetes”, “type 2 diabetes”, “clinical guidelines”, “developed countries”, “developing countries”, “resource poor settings”, “direct costs”, “indirect costs”, “history”, “accuracy”, “competitive bidding”, “market share”, “availability”, “education”, “temperature”, “climate”, “altitude”, “humidity”, “quality of life”, “cost-effectiveness”, “price”, and “cost”. Papers were also accessed from bibliographies of relevant papers. All published papers searched were in English and dates ranged from 2000-2017.

Introduction “Without diagnostics, medicine is blind.”: Alain Mérieux1 A vast and increasing global population has diabetes, ≈415 million people in 2015.2 Hypoglycaemia and hyperglycaemia occur acutely and frequently in diabetes, particularly in insulin treated patients. Long-term glycaemia is also a major determinant of chronic complications. Therefore, home monitoring of blood glucose using meters and strips (“self- monitoring of blood glucose” (SMBG)) is commonly utilised. Diabetes is a unique medical condition in the frequency of home measurements required. Blood glucose meters and strips are also used in a myriad of clinical settings. In High-income countries, continuous interstitial fluid glucose monitoring (CGM) is starting to replace SMBG. However, ≈75% of all people with diabetes live in Low- and Middle- Income Countries2 and can face substantial challenges regarding SMBG - see Figure 1.

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Figure 1: Barriers to blood glucose monitoring

This review collates published information on utility, usage, cost, and access to SMBG tools, and contributes new information on the global market size and composition, financial and non- financial barriers, and import duties. It concludes with recommendations to improve SMBG access, particularly in disadvantaged regions.

History Home glucose monitoring began in the 1940-50s with urine testing, first using Benedict’s solution heated over a Bunsen burner, then effervescent tablets, then urine test-strips.3 SMBG was first used at home by Richard Bernstein in 1969.4 Since then reflectance meters have been replaced by biosensor meters, followed by improvements in speed, miniaturisation, accuracy, and connectivity. Since 2002, continuous glucose monitoring (CGM) systems have become available. Figure 2 (now Figure 1 in Supplementary material) summarises the history of glucose self-monitoring.4–8

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Use of blood glucose meters and strips Health facilities Blood glucose meters and strips are widely used: including for monitoring known diabetes, excluding hypo/hyperglycaemia in neonates, emergency medicine, screening and care for diabetes in pregnancy, parenteral fluid delivery, intensive care, and infections such as malaria (See Pakistan vignette in Appendix). Usage is most common in primary-care. Whilst hospitals often measure glucose in the laboratory, meter and strip use is frequent intra-operatively and for in-patients with diabetes, to give clinicians immediate results. Blood glucose strips are also sometimes used as a first step in diabetes screening, however laboratory confirmation of abnormal results is always indicated.9

Type 1 diabetes The Diabetes Control and Complications Trial (DCCT)10 and its observational follow-up, the Epidemiology of Diabetes Interventions and Complications (EDIC) proved that improving glycaemia reduces microvascular and macrovascular complications.11 The American Diabetes Association (ADA) recommends SMBG at bedtime, pre-meal, throughout exercise, during hypoglycaemia and hyperglycaemia, and before driving for intensive insulin regimens - which may require ≥6-10 tests/day.12 International Society for Paediatric and Adolescent Diabetes (ISPAD) Guidelines note that “glycaemic control is best determined by SMBG as this provides immediate documentation of hyperglycaemia and hypoglycaemia, facilitating strategies to optimally treat and to avoid, out-of-range glucose values”.13 High-Income Country studies confirm SMBG’s benefit: Miller et al.14 documented associations between SMBG frequency and glycaemia for insulin pump and multiple daily injection (MDI) therapy across socioeconomic demographics. Haller et al. found that HbA1c decreases as SMBG frequency increases.15 Results are similar in Low- and Middle-Income Countries. In South Africa, Ziegler et al.16 found an association between SMBG up to 5-times daily and improved glycaemia. Another South African study documented a greater HbA1c reduction with increased SMBG with both insulin 17 pump and MDI therapy. In Brazil, HbA1c levels and SMBG frequency inversely correlated, with no added benefit beyond four tests/day.18 In Mexico, more children adherent to SMBG had HbA1c values <10% (86 mmol/mol) and those achieving the ADA/ISPAD target <7.5% (58 mmol/mol) had a modal frequency of five tests/day.19 Tanzanian20 and Kenyan21 studies also found that SMBG adherence associated with better glycaemia. Regular SMBG performance may also be reasonably expected to have psychological benefits such as feelings of engagement and achievement, and provide knowledge for improvement. The Global TEENS Study found that SMBG frequency was one of three self- management practices independently associated with Diabetes-Specific Health-Related Quality of Life.22 There is limited information on cost-effectiveness for SMBG in type 1 diabetes care. This is the subject of a separate project by our group.

Type 2 diabetes SMBG is beneficial for type 2 diabetes patients on (basal) insulin therapy,23,24 whilst benefit for

138 non-insulin users is unclear. A meta-analysis of Randomized Control Trials suggests a small benefit (mean HbA1c fall 0.17% (2 mmol/mol)),25 while another in large primary care settings did not.26 A Cochrane Review found a small, temporary HbA1c benefit (mean 0.3% (3 mmol/mol) at 6-months) of SMBG, and noted that it may guide diet and lifestyle adjustments.27 Canadian28 and Portugese29 cost-effectiveness studies of SMBG in type 2 diabetes suggest substantial savings with guideline-based policy limits in strip provision in non-insulin dependent patients. Association studies in type 1 and type 2 diabetes could be subject to confounders beyond what investigators have controlled for.

Accuracy Issues International bodies prescribe accuracy requirements for glucose monitoring systems. The “In Vitro Diagnostic Test Systems: Requirements For Blood-Glucose Monitoring Systems For Self- Testing In Managing Diabetes Mellitus (ISO 15197:2015) Standards”30 require that a) ≥95% of measured values are within either ±0.83 mmol/l (±15 mg/dl) of the average measured values of the reference procedure at concentrations <5.55 mmol/l (<100 mg/dl), or within ±15% at glucose concentrations ≥5.5 mmol/l (≥100 mg/dl); and b) 99% of individual values within zones A and B of the Consensus Error Grid for type 1 diabetes.31 The US Food and Drug Administration (FDA) standards require 95% of readings within ±12% for concentrations >4.2 mmol/l (75 mg/dL), ±0.7 mmol/l (12 mg/dl) if <4.2 mmol/l (75 mg/dl), and 98% within ±15% if >4.2 mmol/l (75 mg/dl) and ±0.8mmol/l (15 mg/dl) if <4.2 mmol/l (75 mg/dl).32 A more harmonised approach with verified traceability to higher order standards is recommended.33 In 2012, Freckman et al. found that only 27 of 34 (79.4%) systems fulfilled minimum accuracy requirements of the then-current ISO 15197:2003 standard,34 and only 18 (52.9%) would have met the tighter ISO 15197:2013 criteria.34 A literature review of FDA-approved blood glucose meters summarised the potential adverse clinical and economic impacts from inaccurate systems,35 and referenced a hypothetical study (Budiman et al.) estimating large numbers of severe hypoglycaemic episodes annually with the least accurate systems.36 A Canadian study demonstrated that devices accurate within ±10% vs. ±15% would result in cost- savings for severe hypoglycaemia episodes.37 Another key component of standards is test-strip lot-to-lot variability. Two groups38,39 found that most systems tested did not meet ISO 15197:2003 criteria. Additionally, mean absolute relative differences (MARDs)40 between fingerprick and venous blood glucose levels are higher at low glucose levels.41 Short delays between blood collection and testing can alter results in some systems.42 Freckman et al. found that, relative to usage by trained professionals, lay-user errors such as incorrect blood application, incorrect strip insertion, bent or kinked test-strips, not checking coding, and not removing the finger after the measurement can sometimes cause marked inaccuracies.43 An additional challenge to testing system accuracy is the lack of required independent market evaluations in the US and Europe.33 Current standards only require a one-off premarket evaluation by the manufacturer, rather than formalised postmarket evaluations.33 The FDA relies on performance data provided by manufacturers, but are working towards improved

139 surveillance.44 This is indicative of the wider debate about medical device accuracy and safety in general.45 Given the above, a particular meter reading, e.g. 5.3 mmol/l (95 mg/dl), gives an illusion of precision which may not always be warranted, particularly with low glucose levels.42 Inaccuracy may lead to inappropriate treatments.39 This is an example of an inherent cognitive bias, as most people prefer detailed measurements and assume that the detail is accurate. Quality assessment schemes are recommended for meters used in hospitals9 and the FDA is now recommending stricter standards.32 A quality assessment scheme has also been used in an outpatient setting.46 There is little published on accuracy in real-world settings in less-resourced countries. Low haematocrit, common in such environments, can affect results with some systems.47 Storage according to manufacturers’ recommendations can be difficult in hot and humid climates.48 The upper operating/testing temperature limits of three commonly used systems49– 51 ranged 40-45°C (104-113°F). Two of three systems49,51 recommend storing meters and strips in cool (≤30°C (86°F)), non-humid environments. Haller et al. noted that temperature and humidity affected results in a laboratory, and noted the more clinically relevant question of accuracy in real-world conditions.52 Altitude can also impact readings.53

Global Market The Global information and technology services company IQVIA (formerly Quintiles IMS), provided authors with 2014-2016 global market data for blood glucose test-strips, classified by the EphMRA (European Pharmaceutical Market Research Association) as the Anatomical Therapy Class (ATC) “diabetes test and blood kits”. Data were from 46 countries and two geographic regions, and included the ‘manufacturer selling price’. The price for the end-user will generally be higher due to import tariffs and taxes, and importer, distributor, and retailer margins.39 However, trade discounts for wholesalers or pharmacies may reduce prices.54 There are substantial limitations. Available data are dependent on collection processes, corporate relationships, and parallel trade arrangements (cross-border post-sale movement of stock).55 The IQVIA data collection is implemented through MIDAS56, a market analysis tool that surveys accessible in-country markets. IQVIA does not collect ATC test-strip data for some countries. Full market documentation is more difficult than with pharmaceuticals as there is less information available from ex-factory, official data, and other third party sources. IQVIA informed us of added complications due to varying product licencing procedures and provision arrangements that may lead to incomplete data. Examples include purchase by Direct Mail (Germany), and part self-purchase (Poland). Hence, there were no data available for some countries, including Russia, Spain, and those in Scandinavia. In several other countries, including China, Korea, and France, strip sales were relatively small. Data were not available on the relative proportion of public/private purchases or urban/rural usage. Although an incomplete global picture, we believe this to be the first published data of its kind since 2009.57 In 2016, IQVIA recorded sale of 12.719 billion strips globally: 5.084 billion in the US and 7.635 billion in the ‘Rest of World’. The global market value was (US)$7.602 billion: $4.425 billion (US) and $3.176 billion (Rest of World). The global average ‘manufacturer selling price’ for one

140 test-strip was $0.60, with mean cost in the US $0.87 and in the Rest of the World $0.42. See Appendix, Table 1 for further information on sales from 2014-6. It was not possible to determine if the rise in sales was due to increased per-person usage or instead due to increased prevalence of diabetes, as no country-wide information on average individual usage was available. In 2016, four companies shared 96% of the US market by value (Appendix, Table 2): LifeScan (Johnson & Johnson) (44.7%), Abbott (22.5%), Roche (19.4%), and Ascensia (9.4%). These companies were also the largest producers in the rest of the world: Roche (26.4%), LifeScan (17.4%), Ascensia (16.3%), and Abbott (9.5%). However, a larger portion of the market was shared by other companies (31.4%). The global total was LifeScan (33.3%), Roche (22.3%), Ascensia (17.1%), Abbott (12.3%), with 15.0% sharing the rest of the market. This latter percentage was reported as 10.3% in 2008, from a different source.57 Appendix Table 3 provides information on market share by volume. In the USA, the “big four” companies strip cost ranged $0.64-$1.09. The next six companies’ cost ranged from $0.16-$0.38. In the Rest of World, the “big four” companies’ strip cost ranged $0.37-$0.46, with the next six $0.56-$1.06 (Appendix Table 2). The market share of the “big four” companies in the US rose from 95.1% (2014) to 95.5% (2015) and 96.0% (2016); and in the Rest of World decreased from 70.6% (2014) to 70.2% (2015) and 69.6% (2016). For countries with strip volumes over 20 million in 2016, the presence of the “big four” companies by value ranged from 99.9% in United Arab Emirates to 4.7% in New Zealand (Appendix Table 4). European and Asian markets were more diversified compared to the Americas, possibly reflecting the geographic origin of the companies with smaller market shares (see Table 3 in Appendix). We found no significant relationship between strip costs and combined market-share of the “big four” companies across countries (Pearson correlation (Excel) r2=0.004, p=0.76). Strip costs and a country’s Gross National Income was related (r2 = 0.24, p=0.02).

Competitive Bidding Certain governments implement measures to reduce strip costs. New Zealand has one of the lowest costs ($0.17) (Appendix Table 4), related to strip purchasing through the national health service. IQVIA records acquisition of 60 million strips in 2016, with Pharmaco (Caresens) comprising 93.2%. Competitive bidding was introduced in 201358, and perhaps coincidentally, it was noted that the newly subsidised meters read 0.6 mmol/l (10.8 mg/dl) higher than the previous system, causing some user-anxiety.58 Measurement disparities were not expected to cause significant errors in insulin dosing, but it was observed that this information would have been of value to consumers.58 The Centers for Medicare & Medicaid Services (CMS) in the USA also instituted competitive bidding in 2011.59 This changeover covered Medicare recipients with insulin-treated diabetes receiving mail-order supplies.60 At implementation, those using another company’s system were only notified in writing, instructing them to call or visit the CMS website.61 Medicare claims data showed that SMBG supply acquisition was disrupted, with increased migration to less or no SMBG acquisition.59 Disturbingly, this was associated with increases in mortality, inpatient admissions, and costs.59,61

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Marketing Strategies There is a long history of mergers and acquisitions in this market, and consolidations have “often resorted to a strategy of acquisition, rather than innovation”.8 Generic strips for use on multiple machines have been developed, but with limited accuracy data. However, these have generally been quickly superseded by companies customising meters and strips. Visually-read test-strips are now rarely used62, although they are recommended in emergency and rural settings where meters are not available9 and are simpler to use, particularly for people with less formal education. These strips were often cut in halves or even quarters by users to minimise cost. A meter can become obsolete if consumables are withdrawn from the market or if simpler technologies are phased out which usually necessitates purchase of a new system. People in more resourced countries may send meters to disadvantaged regions, but recipients may not be able to access or afford the strips.62 Inoperable meters are often present in the homes of people with diabetes across the world, as highlighted by a medical anthropologist’s experience in Belize.63 Company revenue from SMBG is mainly from strip sales. The authors are aware that in less-resourced countries, meters are often given away to entice consumers into a new brand, which may or may not be cheaper long-term. Furthermore, such countries are often small- volume markets with less competition: economic principles dictate that prices will usually be higher. Less costly strips ($0.29 in 2015) can however be accessed in some situations from two international pharmaceutical supply non-profits. Meters were $12.90 and $44.10.64 It has been noted that once production lines are set up, strips are not expensive to manufacture. In 2012, PATH noted the manufacturing cost/strip may be as low as $0.06.65

Financial barriers In High-income countries (HICs), access to blood glucose meters and strips is usually adequate. An exception is the United States, where access can be challenging for patients not enrolled in health insurance or patient assistance programs.66 In less-resourced countries, availability of blood glucose testing can be limited even at health facilities: see Pakistan vignette in Appendix, and also Beran and Yudkin.67 We extracted and analysed data on testing availability in primary care facilities from the 2015 WHO survey “Assessing national capacity for the prevention and control of noncommunicable diseases”.68 Country availability was accessed69 and analysed- Figure 2. All High-income countries had complete testing capability, with capacity decreasing as income levels reduced.

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Figure 2: Availability of blood glucose testing in primary health centres

Figure created from raw data from WHO Diabetes Country Profiles.69 Data for this was informed by results from the 2015 Assessing National Capacity for the Prevention and Control of Noncommunicable Diseases Global Survey.68 General availability defined by Survey as >50% presence at health care facilities

The International Diabetes Federation Life for a Child Program Index study70 assessed whether governments could provide, either free or at reasonable cost, at least two strips/day for children with diabetes – a basic provision. This was achieved by 90% of HICs and 35% of Upper-Middle-Income Countries (UMICs), but no Lower-Middle (LMICs) or Low-Income (LICs) Countries. The country with the lowest threshold of Health Expenditure (HE) and Gross Domestic Product per capita (GDP) that could provide strips was Fiji, an UMIC. Fiji was the only one of 53 countries with GDP <$10,000 per capita to achieve provision. Of 46 countries with a HE <$500 per capita, only Fiji and Botswana (another UMIC) met this provision. SMBG supplies are frequently more expensive than insulin, and therefore the largest cost to households in type 1 diabetes care.71 In Mexico, the average annual direct cost was $1,690 with SMBG absorbing 53% and insulin 15%.19 Values in Brazil were 52% for SMBG and 26% for insulin of $1,214 total outpatient costs.72 A German study found SMBG responsible for 28% of the average annual direct costs of €3,745, with pump supplies 25% and insulin 18%.73 In Canada, SMBG contributed 41.6% to total costs of $2,068 (insulin 48.6% and oral antidiabetic drugs 9.8%).74 In USA, SMBG costs accounted for 27% ($750) of total costs of insulin and SMBG related costs.75 In less-resourced countries, public health systems are more likely to provide insulin than test strips, 70 so people with diabetes must purchase test-strips from private pharmacies, at full retail cost,76 where Majikela-Dlangamandla et al. noted strips can sometimes be sold past their expiration dates.62 See also Pakistan vignette in Appendix. Internal data from Life for a Child shows that health insurance schemes in less-resourced countries sometimes provide insulin, but rarely provide strips. Examples include Ghana77 and Bolivia78. This is in contrast to well-resourced countries where out-of-pocket patient costs for strips are usually modest or non-existent. In France and the United Kingdom, strips (capped at

143 prescribed quantities) are free. There is a small co-payment for strips in Australia. Co-payments vary widely across the health system in the United States. Using previously published unit costs71, we compared the annual costs of insulin with SMBG ( twice and four times/day) – ( Figure 3). Two tests/day was more expensive than an annual supply of human insulin (defined as 18 100IU/mL 10mL vials) in most countries, and four tests/day more expensive in all countries: Daily insulin cost ranged $0.25 (Ivory Coast and Pakistan) to $1.23 (Malawi), mean $0.42 and median $0.38. The daily cost of two strips ranged from $0.40 (Somalia) to $2.40 (Burkina Faso), mean $1.02 and median $1.00, with four strips being twice these costs.

Figure 3: Direct costs of insulin and SMGB for families in low-income and middle-income countries

Data from Ogle et al. 201571 *Insulin assumption – 18 vials of 100 IU/ml human insulin (or equivalent volume of 40 IU/ml) **Government provides insulin for free ***Cost updated from previous data

We also calculated these costs as a percentage of 2014 per capita Gross National Income (GNI) figures, atlas method.79 For two test-strips/day, costs ranged from 4% in St Lucia to 129% in Burkina Faso. Mean cost was 41% of GNI and the median 24%. (GNI data were not available for DPR Korea and Somalia).

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A Ghana study noted “given the average Ghanaian income, proper treatment of this disease is an absolute impossibility for the majority of citizens” as strips are not covered by the National Health Insurance Scheme and must be accessed at private retail pharmacies,” where they cost 2-5 Cedis (0.45-1.13 USD) per day.77 A study in India found test-strips to be the highest portion of total outpatient costs when accessed at a state government supported hospital, where they cost 25 Indian Rupees (0.39 USD) per strip.80 In Mozambique and Zambia, it was noted that “only wealthy patients own their own glucose meter”.81 While the high strip costs may render recommended guidelines12,13 unattainable for some in low-resourced settings, monitoring at reduced frequencies, with daily rotation of test- times, is often productively used (Pakistan vignette, Appendix). Despite potential utility in the absence of SMBG, urinary glucose monitoring is rarely used. An exception is in Benin City where investigators recommended that urine testing was better than no testing.82 This mixed type 1 and 2 diabetes study found 72% practiced self- monitoring: 87% tested urine with either reagent tablets or strips, and 13% tested blood with either a meter or visually-read strips.82 Life for a Child has found most countries are not interested in urine testing for social reasons or because they see it as ‘second best’.

Customs and Import Duties Recently, the “Addressing the Challenge and Constraints of Insulin Sources and Supply Study” (ACCISS) reported the global weighted average effectively-applied import tariffs on insulin for retail sale fell from 3.5% in 2004 to 1.9% in 2013, with most countries having little or no tariffs.83 To our knowledge, no previous studies have reviewed import duties or other taxes levied on SMBG tools. From Pitney Bowes’ Global Trade Solutions website84 we extracted “applied Most Favoured Nation” (MFN) duty rates, sales taxes, and additional taxes and duties for ‘Blood Glucose Level Test Strips’ (accessed March 16, 2017). There was data for 149 countries/territories, of which World Bank income classification was available for 129.85 Lower- income countries were under-represented. Table 1 shows fewer HIC than Middle-Income Countries had MFN duties. The nine HIC countries with duties were all Caribbean - ranging from 30% (Turks and Caicos) to 5% (Antigua, Barbados, St Kitts and Nevis).

Table 1: Import duties on blood glucose test strips

Blood Glucose Test Strip Import Duties Countries with Most Range of duty Mean for countries Favoured Nation fee with MFN duty (MFN) duty High-Income Countries (n=64) 17% 5-30% 12% Upper-Middle Income Countries(n=39) 61% 1-15% 6% Lower-Middle Income Countries (n=22) 50% 1-20% 6% Low-Income Countries (n=4) 0% 0-0% 0% All income groups (n=129) 35% 1-30% 7%

Data from Pitney Bowes84, who use HS code 3822 for blood glucose test strips.

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Twenty-four UMICs had MFN duties, with Argentina and Azerbaijan having the highest rates (both 15%). For LMICs, duties tended to be highest in South Asia with Pakistan at 20% (see Pakistan vignette). Eleven LMICs had MFN duty rates. As well as MFN duties, customs taxes and duties and sales taxes can further increase prices. For example, the four LICs for which data were available had no MFN duties. However, Burundi had a 0.5% administrative license fee, 1.15% security tax and 18% sales tax; Rwanda a 5% withholding tax and 18% sales tax, Tanzania an 18% sales tax, and Uganda a 6% withholding tax and 18% sales tax.

Non-Financial Barriers Effective use of SMBG requires substantial numeracy skills, health literacy, and diabetes understanding. The 2002-2003 Global Access to Insulin and Diabetes Supplies Survey noted that a poor level (or complete lack) of diabetes education is an impediment to effective SMBG.86 In the US, independent predictors of SMBG non-adherence included not only higher out-of-pocket costs, but also lower education and difficulty in communicating in English.87 A Tanzanian study found that lower HbA1c was associated with higher parental diabetes knowledge.20 Lower-than- hoped SMBG adherence and glycaemic control for children in the Changing Diabetes in Children program in Cameroon was due to knowledge gaps and individual and population-level determinants, such as lack of formal education.88 The Life for a Child experience introducing SMBG in type 1 diabetes in Rwanda, and some other countries, was that initial usage was low because people with diabetes did not know how to use the tools, and frequently the few and often time-poor health professionals were unfamiliar with teaching the usefulness of SMBG. Families tired of testing and recording results that they did not know how to use, and were not used by physicians (or themselves) to adjust insulin dosages. Task-shifting of education to nurses helped improve usage. Sometimes it is also important to teach others, such as teachers of school-children.77 It is important for clinicians to regularly review patient technique and, if there are accuracy concerns, to compare the patient’s meter against laboratory glucose tests9,12.Large pack sizes can limit uptake in low-resourced countries, as strips usually come in vials of 50 or more, and cost can be prohibitive. Access to and costs of replacement meter batteries may also be challenging. Physical pain can deter SMBG, and this is more problematic in countries where modern multi-depth lancets are not always available, and ‘old-fashioned’ lancets, or injection needles are used for finger-pricking.62 Supplies can be interrupted by natural disasters and humanitarian crises. Life for a Child has also experienced challenges in approvals for donations due to country sanctions and stock crossing some international borders.

Aid interventions and encouragement of sustainability Efforts are underway to improve SMBG access for people with diabetes in less-resourced countries.89 These include in-kind support from Trividia Health Inc., LifeScan Inc., and ACON Diabetes Care enabling Life for a Child to send strips and meters to 35 less-resourced countries.90 Support is provided until age 25, with partial solutions (e.g. donations from Insulin for Life or

146 individual self-sufficiency) for those over 25 years. Other efforts include Roche Diagnostic’s support of the Changing Diabetes in Children Program (in nine countries)91, and assistance in Bolivia92 and Kenya21 from Abbott. Other efforts unknown to the authors may also be underway. Pleasingly, Life for a Child’s support in Fiji, Montenegro and Azerbaijan was withdrawn as national governments assumed responsibility for SMBG supply provision, which, with local efforts, made international donations unnecessary.

Technological advances A new wave in glucose monitoring is interstitial fluid glucose monitoring, including various CGM devices and “flash” glucose monitoring (FGM).93 These advances are limited to those who can afford to self-fund them or whose governments can provide such technology. Therefore, a widening treatment gap looms between those who can access these technologies and those who struggle to access any glucose test- strips at all, and access to less-costly meters and strips must be preserved as these new treatments expand. This is similar to the situation for insulin; various analogue insulins are available94 but access to even human insulin is still problematic in many countries. Less expensive animal insulins were phased out in favour of human insulin, and now there is a risk that access to human insulin will be similarly restricted by promotion of more expensive analogue insulins.94 However, there is a de-facto safety net for long-term SMBG access as these supplies will be needed for non-diabetes purposes and for patients not using CGM (especially in type 2 diabetes). Some groups are investigating lower-cost methods for SMBG such as low-cost inkjet- printed strips95 and silk-weaved blood glucose test-strips.96 These and other novel alternatives will need to overcome challenges of accuracy, shipping issues, supply chains and shelf-life.

Conclusion and Recommendations SMBG is an essential component of type 1 diabetes care and is also indicated for insulin-treated type 2 diabetes and in many other settings. However, these supplies are often unavailable or unaffordable in less-resourced settings, and even when present, usage is compromised by limited diabetes education and other factors. International agencies including the WHO and IDF should prioritise this issue, so that it is better delineated, advocated for, and addressed, as is being done for insulin.81,97,98 Preferential pricing for less-resourced countries, regional pooled procurement schemes, and a WHO pre- qualification scheme could be considered.94 Increased competition may contribute to reduced prices in the future. In January 2017, The WHO issued the first Model List of Essential In Vitro Diagnostics proposal for consultation, scheduled for 2019 publication.99 ‘Glucose testing’ is included as a diagnostic for diabetes99 and we hope this will include SMBG supplies. The ideal glucose monitoring system would be non-invasive. However, until this exists, is globally available and affordable, SMBG systems should have strips that are affordable, available in variable package sizes, have durable batteries, are stable in real-world conditions, and remain available for at least four years (manufacturers should consider the impact of phase- outs). There should be mandated verification against rigorous global accuracy standards with

147 unified evaluations by independent authorities.43 Lancing (preferably multi-depth) devices also need to be available62 The international community could consider funding a prize for low-cost blood or non-invasive glucose monitoring systems. With the rising market penetration of interstitial fluid glucose monitoring, it is imperative that the less-expensive meter/strip alternative remains available and affordable. This is comparable to the situation of human versus analog insulin.94 On a national level, countries should eliminate customs and import duties on these supplies, as has already been done for most essential medicines. Where necessary, the myth that diabetes is a disease of the rich must be addressed,100 and in all countries SMBG should be provided by national health insurance schemes for indicated conditions. Rational expenditure practices should be developed so that the whole diabetes care package – insulin (human only, if funds are limited)94, SMBG, medical care and diabetes education – is available. When competitive bidding is instituted, user perspectives, continued access, and accuracy considerations need to be included to facilitate well-managed transitions.58–60 Further education of both clinicians and diabetes patients is needed in many countries to increase effective SMBG use. Task-shifting from doctors to nurses and other health professionals could be very helpful.101 Finally, where supplies are limited, national guidelines, such as in Pakistan102 should provide guidance on rotating testing times to maximise information collected.

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Acknowledgements We thank IQVIA for providing the global market data on blood glucose test strips, specifically Mike Gains from IQVIA; and also John Grumitt, Vice President Diabetes UK, who facilitated this connection. AJJ is supported by a NHMRC Practioner Fellowship and a Sydney Medical School Foundation Fellowship.

Disclosures statement ELK and GDO report a grant from The Leona M. and Harry B. Helmsley Charitable Trust during the conduct of the study. The Trust did not have any input into the writing of the paper or the decision to submit it for publication. AJJ is on the Abbott Australia (Diabetes) advisory board and has an investigator initiated grant from Gly-Sens, USA. MYA has no disclosure statements.

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For extensive supplementary materials, please see pdf of published paper in Section 12 Appendix A.

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8.10 Paper 10

Ogle GD, von Oettingen JE, Middlehurst AC, Hanas R, Orchard T. Levels of type 1 diabetes care in children and adolescents for countries at varying resource levels. Pediatric Diabetes. 2019;20:95-98.

Authors: 1,2 Graham David Ogle 3Julia Elisabeth von Oettingen 1,2 Angie Middlehurst 1,4 Ragnar Hanas 1,5Trevor Orchard

Institutions: 1 Life for a Child Program, Glebe, Sydney, Australia 2 Diabetes NSW & ACT, Glebe, Sydney, Australia 3 McGill University Health Center – Research Institute, Montreal, Canada 4Sahlgrenska Academy, University of Gothenburg, Institute of Clinical Sciences and Department of Pediatrics, NU Hospital Group, Uddevalla Hospital, Sweden 5Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

Corresponding author: Graham Ogle, [email protected]

Funding sources: This work was partly funded by the Leona M and Harry B Helmsley Charitable Trust.

Institutional review board statement: not required

Conflict of interest statement: None of the authors have any conflicts of interest in regard to this study

Data sharing statement: Not relevant

Abstract Optimal care for children and adolescents with type 1 diabetes is well-described in guidelines such as those of the International Society for Pediatric and Adolescent Diabetes. High-income countries can usually provide this, but the cost of this care is generally prohibitive for lower- income countries. Indeed, in most of these countries, very little care is provided by government health systems, resulting in high mortality, and high complications rates in those who do survive. As lower-income countries work towards establishing guidelines-based care, it is helpful to describe the levels of care that are potentially affordable, cost-effective, and result in substantially improved clinical outcomes. We have developed a Levels of Care concept with three tiers: “Minimal Care”, “Intermediate Care”, and “Comprehensive (Guidelines-based)

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Care”. Each tier contains levels, which describe insulin and blood glucose monitoring regimens, requirements for HbA1c testing, complications screening, diabetes education, and multidisciplinary care. The literature provides various examples at each tier, including from countries where the Life for a Child and the Changing Diabetes in Children programs have assisted local diabetes centres to introduce Intermediate Care. Intra-clinic mean HbA1c levels range from 12.0-14.0% (108-130 mmol/mol) for the most basic level of Minimal Care, 8.0-9.5% (64-80 mmol/mol) for Intermediate Care, and 6.9-8.5% (52-69 mmol/mol) for Comprehensive Care. Countries with sufficient resources should provide Comprehensive Care, working to ensure that it is accessible by all in need, and that resulting HbA1c levels correspond with international recommendations. All other countries should provide Intermediate Care, while working towards the provision of Comprehensive Care.

Introduction Type 1 diabetes (T1D) occurs in children and adolescents across the world, and there are accepted international guidelines for effective management, notably from the International Society for Pediatric and Adolescent Diabetes (ISPAD) [1]. In most well-resourced countries, the resources to achieve such care are essentially fully covered by the respective national health systems [2], although there is a large variation in HbA1c results between high-income western countries [3]. Furthermore, care is improving with advances in insulins, insulin pumps, glucose monitoring, and “closed-loop” systems. However, this is not the case in many middle-income or low-income countries. Insulin, blood glucose tests strips, and other components of care are often unavailable or remain inaccessible, as they must be purchased out-of-pocket by families [2,4-7]. Access to physicians and nurses skilled in T1D management and diabetes education is also very frequently limited [2,4]. These deficiencies in T1D care have profound impacts. Mortality rates are very high in children and adolescents [5,8-11], and for those who do survive, blood glucose control is poor and early chronic diabetes complications are frequent [11-16]. These stark differences in outcomes compared to well-resourced countries are tragic for patients and families and deeply distressing for health professionals. While it is imperative that all countries aim for universal availability of comprehensive guidelines-based care, it is currently unrealistic to expect governments in less-resourced countries to provide all the components of comprehensive care recommended by the ISPAD guidelines [1]. Health budgets are limited and there are many competing demands, such as maternal and child health, infectious diseases, and other chronic health conditions. To help facilitate the work of policy makers, health planners, professional and lay advocates, and the care providers in countries where comprehensive guidelines-based care is mostly inaccessible for young people with T1D, we have developed a “Levels of Care” framework for T1D care (Figure 1). There are three tiers of care – “Minimal Care” (Levels 1A-1D), Intermediate Care” (Levels 2A-2B), and “Comprehensive Care (ISPAD Guidelines)” (Levels 3A- 3D). The tiers concept is based on the “Minimal”, “Standard” and “Comprehensive” Care tiers in the International Diabetes Federation (IDF)’s “Global Guidelines for Type 2 Diabetes” published in 2005 [17]. We replaced “Standard” with “Intermediate” as it more accurately describes a tier

157 that represents an important step towards eventual provision of comprehensive care. For each level, details on insulin therapy, blood glucose monitoring, hemoglobin A1c (HbA1c) testing, complications screening, and diabetes education and multi-disciplinary team care are provided, as well as the expected intra-clinic range of mean clinic HbA1c and mortality and complications.

Figure 1: Levels of type 1 diabetes care in children and adolescents

Levels of Care Tier 1 - Minimal Care “Minimal Care” is defined by that which has been observed and reported in many less-resourced countries [2,5,12,18-21]. In the lowest level, designated 1A, human insulin (if available), is given via two injections daily. In a number of countries, only pre-mixed insulin is used as this is the only insulin provided in the public health system [2,12,15,22]. Health facilities frequently lack any capacity to measure blood glucose [5,23]. Self-monitoring of blood glucose (SMBG) is rarely carried out due to financial barriers [2,5,6,21-23], indeed the cost of two test strips per day is generally higher than the cost of insulin [6,23]. Therefore, blood glucose tests are almost always

158 exclusively carried out during clinic visits, if the measurement is available. HbA1c testing is not likely to be available in any level of the government health system [2,4]. Complications screening is not provided - it is the Life for a Child Program’s [24] experience that even height and blood pressure are not measured at this level of care. There is minimal or no diabetes education, with care provided by an adult physician or a pediatrician inexperienced in the management of T1D [2,19]. This level of care has devastating outcomes. There is a high early mortality from ketoacidosis at onset, due to misdiagnosis or late diagnosis, and later from hypoglycemia and ketoacidosis [2,5,8-11,21]. There are also high rates of early complications [12,14], with devastating long-term complications in some [7,25]. HbA1c levels are high – in Tanzania, means of 14% (130 mmol/mol) [13], 12.6% (114 mmol/mol) [12], and 12.3% (111 mmol/mol) [19] have been reported, and in India 13.0% (119 mmol/mol) has been documented [26]. The next steps in care (Levels 1B and 1C) are the introduction of SMBG at a frequency of two-three tests per week to two tests per day (depending on resources), and human short- and long-acting insulin are given via two injections per day. Education regarding insulin dosage adjustment is critical in optimising use of these insulins. Basic complications screening (usually limited to weight, height, blood pressure, visual acuity, and light touch) is conducted. Care in large centres is usually provided by an adult diabetologist or pediatrician, or a pediatric endocrinologist if available. Once care has progressed from Level 1A to 1B or 1C, reported clinic mean HbA1c levels improve. For example, studies have reported 12.1% (109 mmol/mol) in Kenya [22], 12.0% (108 mmol/mol) in Ethiopia [27], 11.4% (101 mmol/mol) in Cameroon [20], 11.2% (99 mmol/mol) in Rwanda [18], 10% (86 mmol/mol) in Tanzania [13], 9.6% (81 mmol/mol) in Bangladesh [28], and 9.8% (84 mmol/mol) [15] and 9.3% (78 mmol/mol) [4] in Sudan (note that two of these studies [4,27] are older papers from the mid 1990’s). Results will vary according to the particular country situation, whether improved care such as SMBG is available to all or some, and also the age distribution of the clinic population, as HbA1c tends to be higher in adolescents than in pre- pubertal children or adults [7,29-31]. Marshall et al. [18] studied the impact of a systemic, HbA1c-based care and education program in Rwanda (which did not at that stage include widespread SMBG). Mean HbA1c declined from 11.2% (99 mmol/mol) at baseline to 10.2% (88 mmol/mol) at one year and 9.8% (84 mmol/mol) at two years. In Tanzania, mean HbA1c fell from 14% (130 mmol/mol) in 2005 to 10% (86 mmol/mol) in 2012-13 as care improved [13]. Diabetes education is critical: SMBG supplies may be able to be sourced, however health professionals need to be trained to use the results to modify treatment regimens, and in turn teach the families to do the same [23]. Mortality rates fall sharply as care (including management of diabetic ketoacidosis) begins to improve, and thus prevalence increases [9,11,13,25,32].

Tier 2 – Intermediate Care The key feature of Intermediate Care is multiple daily injections (“basal bolus regimen”) [33], accompanied by SMBG and point-of-care HbA1c testing [31], and diabetes education provided by a pediatric or adult endocrinologist and/or a diabetes nurse educator. This is the tier of care

159 that the Life for a Child Program [24] and the Changing Diabetes in Children Program [34] aim to provide through supported centres in less-resourced countries. Both programs generally provide supplies for two blood glucose tests per day, with three or four strips per day being provided in a few countries that already have experience with SMBG (for example from Life for a Child in Bolivia [7]). Human insulin is still recommended in this tier as it is substantially less expensive than analog insulin [35,36]. Although analog insulin is almost universally preferred over human insulin by health care professionals and people with type 1 in well-resourced countries, it is important to note that, despite many studies, improvements in HbA1c levels have not been demonstrated [32,35,36]. It is accepted that analog insulin helps reduce rates of nocturnal hypoglycaemia in well-resourced settings [32,35,37]. Therefore, when funds are limited it is much more important to have more frequent SMBG rather than analog insulin. Increased frequency of SMBG testing has been shown to correlate with a reduction in HbA1c [23,38,39]. If blood glucose supplies are limited, rotation of times of testing can provide added information [40]. In this tier, we also still recommend use of syringes and needles rather than insulin pens due to cost and availability. Insulin delivery by pen is more convenient and less painful than by syringe and needle, and may reduce stigma, and therefore this method is preferred by most people with diabetes, but pens/pen needles are more expensive. Pens also require use of cartridge insulin, rather than the less expensive and more readily available vial insulin preparations [6]. Complications screening is expanded to include more thorough assessment of eyes and feet, measurement of urinary albumin, serum creatinine, and lipids, with treatment as indicated. Appropriate diabetes education with respect to age, language, culture, and literacy level is given, and diabetes camps are held. Diabetic ketoacidosis is managed according to ISPAD guidelines [41]. A 24-hour emergency support call service should also be available, as well as initiatives in peer and school support. Expected mean clinic HbA1c levels, once intermediate care is fully implemented across a clinic, are 8-9.5% (64-80 mmol/mol). Published examples include mean HbA1c of 8.7% (72 mmol/mol) (from 11.4% (101 mmol/mol) a year before) in Cameroon [20], mean 8.3% (67 mmol/mol) (from 13.0% three years before) in India [26], mean 8.5% (69 mmol/mol) and median 8.2% (66 mmol/mol) in Bolivia [7], and mean 8.8% (73 mmol/mol) and median 8.4% (68 mmol/mol) in Mexico [42]. It should be noted that in the Indian study [26], patients were receiving glargine plus human short-acting insulin, and in Bolivia [7] and Mexico [42] some patients were on human insulin and some on analogs. Interestingly, these levels are even similar to those seen in some high-income countries with substantially more resources [3,29,43]. Optimally in this tier, glucagon would also be available, however it is rarely provided by government health services in less-resourced countries [2,44], and the out-of-pocket cost, if it can be purchased at all in these countries, is unaffordable for many. Mortality in this tier of care is substantially lower, with reported rates of 2.0 per 1,000 patient years in Uzbekistan [25] and 2.2 per 1,000 in Bolivia [7]. With HbA1c levels 8-9.5% (64- 80 mmol/mol), long-term complications would also be expected to be much reduced [31,45]. This care is outlined in the LFAC/ISPAD “Pocketbook Guideline for Management of Diabetes in Childhood and Adolescence in Under-resourced Countries [46], and in the Changing Diabetes in Children’s program manual “Diabetes in Children and Adolescents” [47|.

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Within individual countries, thought should be given so that staff at varying levels of the respective health system, (national hospital, provincial hospital, rural health centre etc.) have the training and resources to provide emergency and chronic care and complications screening at the highest practical level. National treatment guidelines tailored to the specific country situation would aid this.

Tier 3 – Comprehensive Care (ISPAD Guidelines) It is beyond the scope of this paper to fully describe comprehensive, guidelines-based care. This is detailed in the ISPAD Clinical Practice Consensus Guidelines 2018 [1]. Multidisciplinary care is provided by a team comprising a pediatric diabetologist, nurse educator, dietitian, social worker and psychologist. The insulin regimen is either basal bolus or, if possible, by continuous subcutaneous infusion with an insulin pump [33]. There is sufficient access to SMBG supplies to permit 4-6 or more tests per day, and in many situations there is access to continuous glucose monitoring (CGM), which has added advantages in some contexts [31]. Most recently, “closed-loop” devices are becoming widely used that link the insulin pump to the CGM device. These advances are represented in Figure 1 by Levels 3A-3D. Full complications screening at the frequency stipulated by the guidelines should be conducted, including, in addition to those outlined in intermediate care, fundus examination by bio-microscopy or photography, and screening for thyroid and celiac disease [45]. Clinic-based, and if possible national, registries should be instituted as part of comprehensive care, with participation in benchmarking efforts such as SWEET [43] providing further benefits. With such care as the norm, mortality is rare [48]. Witsch et al. [43] report a patient median HbA1c of 7.8% (62 mmol/mol) in pooled data from 40 centres participating in the SWEET database (with subjects aged 0-18 years). Clinic median levels ranged from 6.9-9.8% (52-84 mmol/mol). McKnight et al. [30] studied the median HbA1c in population- or clinic-based registries in 19 countries, finding registry median HbA1cs for patients aged <15 years ranged from 7.6-9.4% (60-79 mmol/mol) for those <15 years (11 registries), and 7.5-9.2% (58-77 mmol/mol) for those aged 15-24 years (16 registries). However it should be noted that most patients in the clinics/registries reported in these two papers were not achieving the 2014 ISPAD Clinical Practice Consensus Guidelines target of <7.5% (58 mmol/mol) [49]. On the other hand, continuous improvement of metabolic control is possible on a country-wide level [50]. International targets had recently been updated: the 2018 ISPAD Guidelines [1] state a target of <7.0% (<53 mmol/mol) in most clinical situations when comprehensive care is available, and <7.5% (<58 mmol/mol) when there is no access to analog insulins, advanced insulin delivery systems, or frequent or continuous glucose monitoring. Some high-income countries (U.K [51], Sweden [52]) have set the even lower target of 6.5% (48 mmol/mol) in most clinical situations. The challenge, even in well-resourced countries, is to ensure that comprehensive, guidelines- based care is effectively delivered to all people with T1D, not just those who access the leading clinics or who can afford more comprehensive private health insurance plans, but also to those in regional and rural areas and those from disadvantaged socio-economic situations.

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Conclusions and Recommendations All people with T1D deserve quality care. In countries that can afford it, comprehensive, guidelines-based care should be provided through the respective government health service. Currently however, many less-resourced countries are only providing what we have defined as “Minimal Care”, which has a high morbidity and mortality. We therefore encourage and recommend that less-resourced countries support “Intermediate Care”, an approach that is substantially less expensive than Comprehensive Care but can still achieve markedly improved outcomes. The key components of Intermediate Care are human insulin in a basal bolus regimen, SMBG, point-of-care HbA1c testing, diabetes education, basic complications screening, and access to a doctor and nurse experienced in T1D care in young people. Countries with the capacity to provide Comprehensive Care should do so, work to ensure that it is accessible by all in need, and that the resulting HbA1c levels achieved are in line with the international recommendations [30] or further refined national guidelines. All other countries should provide Intermediate Care while working towards the provision of Comprehensive Care. Formal assessment of cost-effectiveness of Intermediate versus Minimal Care in less-resourced countries would be very helpful in advocacy activities, and we are working on this as a separate project. Access to SMBG is a profound issue for improving type 1 diabetes care in less-resourced settings, and national and international advocacy and innovative approaches are needed to address this issue [23]. We also recommend that both mean and median data be presented in papers to aid comparisons, that HbA1c levels are presented in both IFCC (mmol/mol) and DCCT/NGSP levels (%), and that blood glucose is presented as both mmol/l and mg/dl. In conclusion, we hope this stratified set of levels of care will help not only in the standard description of care across the world, but also provide a framework that will enable health providers and planners to set treatment goals and fund and implement plans to meet those goals.

Acknowledgements This work has been partly funded from a grant by the Leona M and Harry B Helmsley Charitable Trust to the IDF Life for a Child Program. We thank Emma Klatman for comments on the text and assistance with the preparation and submission of the manuscript.

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8.11 Paper 11

Ogle GD, Abdullah M, Mason D, Januszewski A, Besançon S. Insulin storage in hot climates without refrigeration – temperature reduction efficacy of clay pots and other techniques. Diabetic Medicine 2016;33:1544-1553.

Authors: • Graham D. Ogle FRACP, International Diabetes Federation Life for a Child Program, and Diabetes NSW, Australia. • Mohamed Abdullah FRCPCH, Sudan Childhood Diabetes Centre, Khartoum, Sudan. • David Mason BSc, International Diabetes Federation Life for a Child Program, and Macquarie University, Australia. • Andrzej S. Januszewski PhD. NHMRC Clinical Trials Centre, University of Sydney, Australia. • Stéphane Besançon, Santé Diabète, Bamako, Mali. Corresponding author: Graham D. Ogle FRACP, International Diabetes Federation Life for a Child Program, and Diabetes NSW, Australia.

Word count, abstract: 250 Word count, full text: 3,258

Bulleted novelty statement • Thousands of families in less-resourced countries use clay pot evaporative cooling to store insulin in the absence of refrigeration, and yet there is little published on efficacy. • This is the first study comparing different traditional devices (from seven countries) and manufactured insulin cooling bags. • Results show these devices can achieve temperatures at/near room temperature, suggesting that storage for 2-5 months is safe. • The critical importance of humidity (previously unaddressed in the literature) is reviewed, and a formula is included to predict efficacy in a given climatic situation. • The paucity of published data on human and analog insulin thermostability is highlighted.

Abstract Aims Insulin loses potency when stored at high temperatures. Various clay pots part-filled with water, and other evaporative cooling devices, are used in less-resourced countries when home refrigeration is unavailable. This study examined cooling efficacy of such devices. Methods Thirteen devices used in Sudan, Ethiopia, Tanzania, Mali, India, Pakistan, Haiti (11 clay pots, a goat skin, a vegetable gourd, and a wet-sand filled bucket), and two identical commercially

167 manufactured cooling wallets were compared. Devices were maintained according to local instructions. Internal and ambient temperature, and ambient humidity were measured by electronic loggers every five minutes in Khartoum (88 hours), and, for the two Malian pots, in Bamako (84 hours). Cooling efficacy was assessed by: average absolute temperature difference (internal vs. ambient), and % maximal possible evaporative cooling (allowing for humidity). Results During the study period mean ambient temperatures and humidities were 31.0oC/32.9oC (Khartoum/Bamako) and 32.0%/39.8% respectively. All devices reduced temperature (p<0.001) with mean (SD) reduction from 2.7±0.5oC to 8.3±1.0oC depending on the device. When expressed as % maximal cooling, device efficacy ranged from 20.5-71.3%. On cluster analysis, the most efficacious devices were the goat skin, two clay pots (from Ethiopia and Sudan), and the suspended cooling wallet. Conclusions Low-cost devices used in less-resourced countries reduce storage temperatures. With more efficacious devices, average temperatures at/close to standard room temperature (20-25 oC) can be achieved, even in hot climates. All devices are more efficacious at lower humidities. Further studies are needed on insulin stability to determine when these devices are necessary.

Introduction Children and adults with type 1 diabetes require exogenous insulin for survival, and many more people with type 2 diabetes also require daily insulin injections. Administered insulin must have predictable potency, otherwise unexpected and potentially dangerous blood glucose excursions can ensue. Insulin is temperature-sensitive, with increasing degradation with rising temperatures[1,2,3], although publications on the effect of temperature on newer insulins are scant[4-7]. All manufacturers of human insulin direct that insulin be stored in refrigerators (at 2-8o C, never frozen), almost always with a maximum of one month usage/storage at standard room temperature (20-25oC)[4,5,8]. For analog insulins, glargine can be kept for four weeks at <25o C[4], detemir for four weeks at <30o C [5], and degludec for eight weeks at <30o C[9]. This requirement is a challenge for many thousands of families in low- and middle- income countries with hot climates, who do not have home refrigeration[10-21]. The International Diabetes Federation Life for a Child (LFAC) Index study[21] reported that, in 30 of 37 low- and lower-middle income countries, at least 33% of families with children with diabetes did not have a home refrigerator. Furthermore, insulin access may be problematic due to cost, intermittent pharmacy supplies, quarterly clinic visits, and travel costs to attend clinics[21-23]. These factors can increase the time that insulin is unrefrigerated to three months or more, and accentuate the need for cooling systems. Sometimes a solution is a neighbour’s or local shop’s refrigerator[10,11,13,17]. In many other cases in Africa, Asia and the Caribbean, insulin is stored in water-filled clay pots or other traditional storage devices, of various designs, using evaporative cooling[10-20]. Such clay pots (‘zeer’ pots, ‘matka’) are traditionally used in hot climates to keep water and foodstuffs cool[24,25].

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However there are few studies on the cooling efficacy of devices used for insulin storage, and these have conflicting results and do not compare different designs or take humidity into account[12,14,16,20]. The level of humidity is critical in evaporative cooling, where the “wet-bulb” temperature is the physical concept describing the lowest temperature that can be achieved by evaporative cooling at any particular ambient temperature/humidity pairing[24,26]. When humidity is 100%, the wet-bulb temperature is the same as the ambient temperature – no evaporative cooling is possible[24,26]. As humidity declines the wet-bulb temperature declines compared to the ambient (“dry-bulb”) temperature[24,26]. The International Diabetes Federation (IDF) Life for a Child Program (LFAC) conducted a “Clay Pot Olympics” in Khartoum, Sudan to determine if pots and similar traditional evaporative cooling devices were efficacious in reducing temperature. A manufactured insulin cooling wallet was also studied in the same way.

Methods Figure 1 is flow diagram outlining the study methods.

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Pots and other cooling devices The pots and other evaporative cooling devices were sourced from LFAC program partners in seven countries: Sudan, Tanzania, Ethiopia, Pakistan, India, Haiti, and Mali. All device styles tested were in regular use. In addition, two insulin cooling wallets were purchased (“Large Wallet” types, FRIO UK Ltd, Little Treffgarne, Haverfordwest, U.K.). 15 cooling techniques were studied – clay pots from Sudan (three types), Pakistan, Tanzania, Ethiopia, India, Haiti, and Mali (two types); a vegetable gourd from Sudan; an animal skin from Sudan; a sand-filled bucket from Ethiopia; and two cooling wallets – one positioned suspended, the other prone (to examine whether the higher surface (evaporative) area of the suspended bag made a difference). The devices were named by country of origin, with sequential numbering when there was more than one device from a country. Table 1 describes the device features, and Fig. 2 shows the 13 non-commercial devices. Instructions about filling the devices, and refilling times, were provided by each centre and followed by the study investigators. The cooling wallets were maintained per the manufacturer’s instructions.

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Table 1: Description of cooling devices

Cooling Description Lid Dimensions Weight Instructions device (height x (kg) maximum diameter (cm)) Sudan 1 Porous clay pot filled with None 53 x 39 12.7 Topped up with water when water, placed on iron tripod necessary – in this study twice and covered by hessian bag. in Period 1 and once in Period 2 Water dripping into smaller clay vessel sitting on sand underneath (thermometer in smaller vessel). Sudan 2 Non-porous, suspended Woven lid 22 x 18 1.3 Topped up with water when vegetable gourd, filled with necessary (not needed during water. this study) Sudan 3 Non-porous, round-bottomed Clay lid 20 x 19 2.8 Topped up with water when clay pot with handles filled necessary (not needed during with water. Placed on sand. this study) Sudan 4 Semi-porous clay pot filled None 18 x 13 2.2 Topped up with water when with water. necessary (not needed during this study) Sudan 5 Goat skin, turned inside out None 60 x 19 2.15 Topped up with water when and openings sewn together. necessary (not needed during Filled with water - a knot tied this study) around the last opening. India 1* Semi-porous clay pot with Clay lid with cup 18 x 19 2.9 Topped up with water when inner and outer walls, cont. water necessary. In this study the pot merged at base and forming (draining over was topped up once in Period 1 a brim at the top. Water the lid to keep it and nil times in Period 2,, whilst poured in the brim. wet). the cup on the lid was topped Thermometer in inner pot up twice daily. (no water). Tanzania 1 Round-bottomed non-porous Clay lid 18 x 18 2.8 Topped up with water when clay pot covered by cement, necessary (not needed during placed on pile of dry sand this study)

Pakistan 1 Porous clay pot (cylindrical) Clay lid, poorly 25 x 23 4.8 Water changed each morning filled with water fitting Haiti 1 Semi-porous clay pot filled Clay lid 11 x 14 1.8 Topped up with water when with water. necessary (not needed during this study) Ethiopia 1 Clay pot with “hips” filled 2/3 None 43 x 25 5.4 Topped up with water when with water. Glazed (non- necessary (not needed during porous). this study) Ethiopia 2 Bucket filled with wet sand, None 33 x 29 34.7 Sand wet as necessary (not with a cut-off lower part of a (including needed during this study) plastic drinking bottle in wet sand) middle (no water), insulin placed in there

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Mali 1 Clay pot part-filled with Clay lid 32 x 23 4 kg Topped up with water when water, wet sand around the necessary (not needed during base of the pot, clay lid this study) Mali 2 Clay pot (identical to Mali 1), Clay lid 32 x 23 4 kg Topped up with water when plastic lid necessary (not needed during this study) United FRIO cooling wallet, Not relevant 21 x 14 <0.5 kg Wet before each study Period Kingdom 1 Suspended United FRIO cooling wallet lying on Not relevant 21 x 14 <0.5 kg Wet before each study Period Kingdom 2 mat) * Flaw in middle section upon arrival, was repaired with cement well before study.

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Figure 2: Cooling devices studied

Cooling devices studies. (A) The devices that were studies in Khartoum except for Ethiopia 2, Sudan 5, and the cooling wallets. (B) the goat skin freshly filled with water. (C) The goat skin in use.

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Site and setup The study of all devices, except for the two Mali pots, was conducted at the same time in a well-ventilated internal room, with open windows, in a building at the Sudan Childhood Diabetes Centre, Khartoum, Sudan. There was no direct sunlight. The pots were placed at least 80 cm apart in a grid arrangement to maximise airflow. The three cooling devices needing suspension (Sudan 2, Sudan 5, and an insulin wallet) and the one external temperature and humidity logger were suspended 45-60 cm apart. There was also a minimum of 80 cm between the pots and any walls or other objects. The study of the Mali pots was conducted in a house in Bamako, Mali as pots broke twice during air transport. The temperature and humidity loggers used were some of the same devices used in Sudan.

Temperature and humidity measurements Internal temperatures of each clay pot and the FRIO wallet were monitored by a MicroLite II high accuracy USB temperature logger (Fourtec, Rosh Ha’ayin, Israel). The thermometer was placed in a small plastic bag in the internal space of each cooling device. The temperature was logged every five minutes. The temperature loggers were programmed to begin recording at a pre-set time, and kept together in the same environment before placement in the cooling devices. The start time was synchronised between loggers to ensure simultaneous temperature recording. External temperature and relative humidity were recorded with a MicroLite 2 USB Temperature and Humidity Logger, at the same five-minute intervals. The logger was suspended in the immediate vicinity of the devices. The devices were prepared according to the instructions received and then left principally undisturbed with the lids secure (if they had lids) for 44 hrs (Period 1), aside from checking water levels and refilling as needed. Testing was then repeated for a further 44 hours (Period 2). For the Mali pots, the total testing period was 84 hours (2 x 42 hours). After preparation, the devices were left to equilibrate for 90 minutes before each period of testing. Data from each individual logger were uploaded to a personal computer. The 15 thermometers used were also tested against each other for 18 measurements at five-minute intervals. To adjust for inter-thermometer variability, the mean deviance of each thermometer from the mean temperature across all thermometers was calculated. This deviance was added or subtracted (as appropriate) to/from each individual thermometer’s measurements.

Calculation of Relative cooling effect The Wet Bulb Temperature (theoretical minimum temperature at a given temperature and humidity) was determined by the formula of Stull[27]. The maximum possible cooling effect was calculated by subtracting the Wet Bulb temperature from the study room temperature. The relative cooling effect for each cooling method was calculated by dividing the [difference between the temperature within the device and the study room temperature], by the [maximum cooling effect] (expressed as a percentage). A perfect cooling system would replicate Wet Bulb Temperature and give a relative cooling effect of 100%.

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To estimate the impact in the warmest months of the year, the mean ambient temperature, humidity, and wet-bulb temperatures were calculated for the seven cities from where the devices were sourced (Khartoum, Nagpur, Dar es Salaam, Karachi, Port au Prince, Addis Ababa, Bamako). The mean of the monthly means of the three warmest months was used (data from www.climatemps.com[28]).

Statistical analyses Data were analysed using Statistica for Windows (version 13, Tulsa, USA). The difference between each device’s interior temperature and the external ambient temperature was analysed using an unpaired t-test. All temperature and relative cooling effect calculations for each pot across the two testing periods were combined and analysed using cluster analysis, to determine the similarities/differences between the performance of each device. Two sets of cluster analysis were performed – one for the temperature differences between ambient air and the interior of the device; and the other for the relative cooling effect calculations. Euclidean distances between data points (temperature difference vs. ambient; and relative cooling effect) at each time point were calculated, and the single-linkage method was used to identify groups of devices with similar cooling performances. In the single linkage method, the distance between two clusters is the distance between two closest objects in different clusters (“nearest neighbours” method)[29,30]. In total, 15 variables (representing devices) and 1,010 cases (representing individual paired measurements of temperature difference and relative cooling effect) were used. After preparation of the dendrograms, the numbers of clusters were determined using the Mojena rule[31,32], and the cluster members (i.e. devices) were determined using the k-means method[33]. Differences in average hourly measurements (temperature difference and relative cooling effect) between clusters (combined to one 24-hour period for the duration of the experiment) were calculated using analysis of variance with a post-hoc Bonferroni test.

Results 1. Inter-thermometer variability The deviance between the thermometers was small – compared to the mean for all 15 thermometers, the mean deviance of the individual thermometers ranged from -0.30oC to +0.36oC (SD 0.16oC). The mean temperature during this test was 30.75 oC. 2. Raw temperature and humidity results For Sudan, temperature over the 88-hour period ranged from 29.1-33.4oC (mean±SD 31.0±0.7oC) and humidity 23.6-48.6% (mean±SD 32.0±4.7%). For Mali, the respective figures for temperature were 31.9-33.8oC (mean±SD 32.9±0.4oC), and for humidity 32.0-50.1% (mean±SD 39.8±3.6 %). Fig. 3a shows the temperature results for the 13 devices tested in Sudan, and Fig. 3b the two devices tested in Mali. All devices achieved internal temperatures that were always lower than ambient air temperature (p<0.001). All devices adjusted promptly to changing temperatures.

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Figure 3: Temperature results for the 13 devices tested in Sudan (A) and Mali (B)

3. Temperature difference and relative cooling effect The difference between the external ambient temperature and the temperature inside each device varied from 2.7±0.5 ºC to 8.3±1.0 ºC (Table 2). On cluster analysis, the devices fell into four groups (Table 2 and Fig. 4). There were four devices in the most efficacious group: Sudan 5 (the goat skin), Sudan 4 and Ethiopia 1 (both clay pots), and the suspended cooling wallet. Relative cooling effect ranged from 20.5±5.0% to 71.3±5.3% (see Table 2). Cluster analysis for the relative cooling effect found identical groups to those for temperature difference.

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Table 2: Temperature reductions achieved by each cooling device

Absolute temperature Relative cooling effect Device reduction (oC) (%) Sudan 5 8.3 ± 1.0* 71.3 ± 5.3

Ethiopia 1 8.0 ± 1.1* 68.4 ± 5.7

Sudan 4 7.6 ± 1.2* 65.3 ± 4.6 Group 1 Group

Cooling wallet – suspended 7.5 ± 1.0* 63.7 ± 4.6

Pakistan 7.0 ± 1.0* 59.8 ± 5.0

India 7.0 ± 1.1* 59.6 ± 6.4

Cooling wallet – lying 6.8 ± 1.0* 57.7 ± 4.4 Group 2 Group

KHARTOUM Sudan 1 6.7 ± 1.1* 56.9 ± 7.4

Sudan 3 5.5 ± 0.7* 46.2 ± 5.4

3

Group Group Haiti 5.0 ± 0.6* 41.2 ± 3.6

Sudan 2 3.6 ± 0.9* 28.4 ± 8.5

Tanzania 3.5 ± 1.0* 28.1 ± 7.7

Ethiopia 2 2.7 ± 0.5* 20.5 ± 5.0

Group 4 Group

Mali 1 3.1 ± 0.5* 29.8 ± 0.6

BAMAKO Mali 2 3.2 ± 0.4* 29.8 ± 0.3 * P = <0.001 vs. ambient temperature

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Figure 4: Mean temperature difference (from ambient) and relative cooling effect (RCE) for each group on cluster analysis.

B

Absolute temperature difference (0C) between the ambient temperature and the four clusters of devices. B: Relative cooling effect (% maximum cooling potential) for the four clusters of devices.

4. Potential impact in warmest months Assuming a relative cooling effect of 62.9% (the average for the eight devices in the two best performing groups in Table 2), we mathematically modelled the impact of a device during the warmest three months of the year in the seven cities where the non-commercial devices were sourced from. Table 3 shows the average temperature and humidity for the hottest three months, as well as the average daily maximum temperature, the wet-bulb temperatures, and the potential reduction from the cooling device.

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Table 3: Impact of an efficacious cooling device in the hottest period of the year in each city

*Assuming the cooling device has a relative cooling effect of 62.8% (the average of the eight devices in the two best performing groups on cluster analysis

Discussion Our study has documented and compared the temperature-reducing efficacy of 13 traditional cooling devices used for insulin storage in seven hot countries in which many families do not have access to home refrigeration, and also a commercially-manufactured cooling wallet. The study is novel as devices from multiple countries were studied, the impact of humidity was taken into account, and it is the first peer-reviewed study on the manufactured insulin wallet. We demonstrated that a range of low-cost devices used in less-resourced countries are efficacious in reducing insulin storage temperatures. The most efficacious devices were the goat skin (with its large evaporative area), two porous pots without lids, and the suspended UK-made cooling wallet. Devices that were non-porous (cemented or glazed pots, or the vegetable gourd) were substantially less efficacious (with the exception of the large glazed open pot from Ethiopia). The most efficacious devices did not have lids, thereby increasing the area and ease of evaporation, although some pots with lids performed almost as well as the devices in the most efficacious group. The relative cooling effects achieved in this study are comparable to the 55-70% values reported for direct cooling methods used for cooling water or fruit and vegetables[24]. Actual temperature achieved is dependent upon both ambient temperature and humidity. The relatively small variation of the relative cooling effect values (seen in the low SD values) for each device demonstrates that all devices responded appropriately and predictably to changes in both temperature and humidity. Cooling also depends on heat and mass transfer coefficients, impacted by the surface area and shape of the pot, thermal conductivity of the particular clay used, volume of water, and other factors[34]. Our study was not designed to investigate the relative impact of these variables. Four previous reports on the efficacy of (individual) clay pots have been generally positive. Shaibi et al.[20] studied an unglazed porous clay pot in Saudi Arabia. The inside of the pot was a mean of 8.7oC cooler than storage in the shade (with ambient temperature 29-43oC). There was a small, non-statistically significant fall in glucose-lowering effect of insulin stored in the clay pot compared to the refrigerator after six weeks. Allen[14] in Uganda assessed a

179 spherical porous clay pot filled with 7-10 litres of water in a shaded well-ventilated position. Water maintained a temperature of 15-17oC, despite rises in ambient temperature up to 41oC. Use of the pots reduced the need to increase dosages in the last two weeks of the 12-week period, and there was less morning glycosuria and nocturia. Gill et al.[13] found a reduction of only 0.8oC from a clay pot in South Africa, with ambient temperature 23.4oC and a two-hour equilibration. The Nagpur pot-within-a-pot design used in this study has been reported as keeping a temperature of 21-25oC when the ambient temperature is 42-48oC[16]. None of these studies reported humidity or assessed wet-bulb temperatures, and so it is impossible to properly assess how efficacious the devices were in reducing temperature, as results would be expected to vary substantially under different humidities[24,26]. The wider context for this study’s findings is that insulin potency is temperature dependent, with an exponential decrease at higher temperatures. Pingel and Volund[1] showed that for animal-derived lente insulin biological potency after storage at 26oC for 2 months and 5 months reduced by ≈1% and 2% respectively, 2%/5% at 30oC, 6%/15% at 37oC, and 20%/40% at 43oC. For actrapid, the corresponding figures were <1%/<1% at 26oC, <1%/2% at 30oC, 2%/5% at 37oC, and 5%/11% at 43oC. Comparable findings were reported by Storvick and Henry[3], with animal-derived NPH insulin retaining potency (≥95% original level) for ≥12 months when stored at 25oC. However, despite calls for such information, there are little comparable published data on human or analog insulin[4-7]. In Grajower et al.[4], companies reported “insulin” losing <1% potency at 25oC for one month, and glargine having a slight loss in activity at 25oC for nine months. Almost all recommended maximum storage times for human insulin at standard room temperature (20-25 oC) are ≤ one month[4,5,7]. We found only three studies in the literature concerning human or analog insulin. Sixty days of storage in Bamako, Mali at 4oC and at ambient temperature (25o-34oC) led to no difference in potency for human insulin[35]. In India[15], 28 days storage at 32oC and 37oC reduced the concentration of regular insulin by 14%/18% respectively, and for biphasic insulin of 11%/14%, compared to insulin stored at 5oC and 25oC. The decrease in potency (tested in rabbits) was less than the decrease in concentration, likely due to biologically active metabolites. Silva et al.[6] found that chromatographs of mixed human insulin and insulin detemir were altered after 42 days storage at room temperature. Based on the respective average maximum temperature and average humidity of the hot-climate cities involved in this study, our results indicate that if one of the eight most efficacious devices was used (with a mean relative cooling effect of 62.8%), peak storage temperatures of ≤320C could be achieved in five of these six cities during the warmest 3 months, with an average storage temperature estimated as 25-280C (at or just above standard room temperature). The exception is Karachi, where it is very humid in the hottest months. If insulins used today respond to temperature in the same way as insulins studied by Pingel and Volund[1], insulin stored in pots and other devices with a relative cooling effect of 62.8% should lose no more than 2% potency in five months – which should be safe for standard usage in less-resourced countries. The devices may therefore not be needed at all in cooler cities such as Addis Ababa (Ethiopia), and may not be of significant benefit if a location’s hot months are also humid (such as Karachi (Pakistan) or Port-au-Prince (Haiti)). Utility will vary widely across a country – for

180 instance both Ethiopia and Pakistan have areas with extraordinarily hot and dry weather. All devices tested responded promptly to changes in temperature. The potential utility of a clay pot or other device in a particular location can be predicted by calculating the wet bulb temperature using an online psychrometric calculator[36], and then using the equation[24] achieved temperature = ambient temperature – (relative cooling effect multiplied by (ambient temperature – wet bulb temperature)), with relative cooling effect expressed as a percentage, 62.8% being a reasonable assumption if one of the eight most efficacious devices is used. A simplified version of this study protocol, along with the equation above could be used to compare different designs used in a particular country, or designs not tested in this study, such as the standard pot-in-a-pot design that uses wet sand between the two pots, with the inner pot dry[25,37]. A dry inner pot would be easiest to manage, avoiding needing to use watertight bags to keep the insulin vials and packaging dry. The strengths of the study include the frequent multiple measurements over a long period; simultaneous comparison of a number of traditional, and a modern device; and simultaneous measurement of humidity, which permitted a standardised assessment of how well the pots performed (using the relative cooling effect). Our study has some limitations. Pots were studied in two locations, however the same robust methodology was used, climatic conditions were similar, and the relative cooling effect determination allows for varying climactic conditions. The devices were not studied in the family homes, but given the simple requirements for such a device – a well-ventilated place in the shade, which we replicated - we believe that results would be very similar. The range of temperature and humidity studied did not cover all temperature/humidity scenarios that were modelled when assessing the efficacy of the devices in the hottest months in their city of origin. However, given the brisk response of each device to ambient temperature and humidity change (as evidenced by the raw temperature data, and tight SD of the relative cooling effect respectively), and the immutable underlying physical principles involved, we believe that our mathematical extrapolations to predict efficacy in the sites where the pots are used are sound. In conclusion, we found that a number of clay pots and other cooling devices used in less-resourced countries can reduce storage temperatures to or near standard room temperature levels. Some other devices were less efficacious. Use of one of the more efficacious designs should make insulin storage safe for five months or more, assuming current insulins are no less thermostable than animal insulins. We also have developed a method of assessing efficacy and then predicting temperature reduction at different levels of temperature and humidity. Investigations of the influence of evaporative surface area, shape of the pots, type of clay, and volume of water in the pots would provide further useful information on how to optimise cooling. Further studies on stability of human and analog insulins under different temperature conditions are very much needed to determine when use of these pots is warranted, and when families can be reassured that storage in a cooler part of the house is adequate. Such data could help people with diabetes even in developed countries as insulin may not need to be discarded after one month. Finally, development of a thermostable insulin preparation would

181 solve this problem completely, and obviate the need for the cold chain at all levels of insulin distribution and use.

Acknowledgements We thank the following centres for providing cooling devices: Dr. Sharad Pendsey (DREAM Trust, Nagpur, India), Misrak Tarekegn (Ethiopian Diabetes Association, Addis Ababa, Ethiopia); Dr. Nancy Larco (FHADIMAC, Haiti), Dr. Asher Fawwad (BIDE, Karachi, Pakistan), Lilian John (Tanzanian Diabetes Association, Dar es Salaam, Tanzania). We also thank Ms. N Sanosi and others from the Sudanese Childhood Diabetes Association in Khartoum, who sourced the pots and hosted the study; and Prof. Alicia Jenkins (NHMRC Clinical Trials Centre, University of Sydney), and Prof. Martin Silink (Children’s Hospital Westmead, Sydney), for advice and comments on the manuscript. This study was presented as an oral presentation at the International Society for Pediatric and Adolescent Diabetes meeting in Brisbane, October 2015, and as a poster at the International Diabetes Federation World Diabetes Congress in Vancouver, November 2015.

Funding The study was funded with support from The Leona M. and Harry B. Helmsley Charitable Trust. ASJ is funded by the NHMRC Clinical Trials Centre.

References 1. Pingel M, Vølund A. Stability of Insulin Preparations. Diabetes 1972;21:805-813. 2. Brange J. Galenics of insulin. Berlin: Springer-Verlag; 1987 3. Storvick WO, Henry HJ. Effect of Storage Temperature on Stability of Commercial Insulin Preparations. Diabetes 1968;17:499-502 4. Grajower MM, Fraser CG, Holcombe JH et al. How long should insulin be used once a vial is started? Diabetes Care 2003;26:2665-2669. 5. Grajower MM. How long can a vial of insulin be used after it is started?: Where are we 10 years later? Endocr Pract 2014;20:188-190. 6. Silva MA, Chuoung M, Kerr S, Cabrera A. Stability of two long-acting insulin formulations after 28 days. J Pharm Prac Research 2013;43:37-40. 7. Molitch ME. How long should insulin be used once a vial is started? – Response to Grajower et al. Diabetes Care 2004;27:1240-1241. 8. Keller KJ. Insulin storage and stability update. S D J Med 2003;56:303-304. 9. Novo Nordisk. Degludec – summary of product characteristics. www.ema.europa.eu/docs/en_GB/document_library/EPAR_- _Product_Information/human/002498/WC500138940.pdf. Accessed 4th May, 2016. 10. Famuyiwa OO. Insulin storage by diabetes patients. International Diabetes Digest 1996;7:28. 11. Puepet, Mijinyawa BB, Akogu IA. Insulin storage by patients with diabetes in Jos, Nigeria. J Med Tropics 2007;9:37-40. 12. Gill GV, Price C, English P, Eriksson-Lee J. Traditional Clay Pots as Storage Containers for Insulin in Hot Climates. Tropical Doctor, 2002; 32:237-238.

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13. Gill GV. Stability of insulin in tropical countries. Tropical Medicine and International Health, 2000;5:666. 14. Allen SC. A cool storage pot for insulin in rural Africa. Med J Zambia 1992;16:83-84. 15. Vimalavathini R, Gitanjali B. Effect of temperature on the potency and pharmacological action of insulin. Indian J Med Res 2009;130:166-169. 16. Pendsey S. Keeping insulin cool naturally – the DREAM Trust storage system. Diabetes Voice 2006;51:19. 17. Newman B, Wilkinson D, Gill G. Insulin storage in rural South Africa, Diabetes International 1999;9:52. 18. Harries A, Maher D. Home insulin storage by patients with diabetes mellitus in Blantyre, Malawi. International Diabetes Digest 1994;5:104. 19. Seyoum B, Abdulkadir J, Feleke Y, Worku Y. Insulin storage by diabetic patients in Ethiopia. International Diabetes Digest 1998;9:43-44. 20. Shaibi KA, Falata W, Sayes N, et al. Storing insulin in a clay pot in the desert causes no loss of activity: A preliminary report. Ann Saudi Med 1999;19:547-549. 21. Ogle GD, Middlehurst AC, Silink M. The IDF Life for a Child Program Index of diabetes care for children and youth. Pediatric Diabetes 2015; doi 10.1111/pedi.12296. 22. Beran D, Yudkin J, De Courten M. Access to care for patients with insulin-requiring diabetes in developing countries: Case studies of Mozambique and Zambia. Diabetes Care. September 2005: 28 (9) 2136-2140. 23. Metta M, Haisma H, Kessy F, Geubbels E, Hutter I, Bailey A. “It is the medicines that keep us alive”: lived experiences of diabetes medication use and continuity among adults in Southeastern Tanzania. BMC Health Services Research 2015;15:111. 24. Basediya AL, Samuel DVK, Beera V. Evaporative cooling system for storage of fruits and vegetables - a review. J Food Sci Technol 2013; 50:429-442. 25. 2000 Rolex Awards for Enterprise. Mohammed bah Abba – Ancient technology preserves food. www.rolexawards.com/profiles/laureates/mohammed_bah_abba/project. Accessed 29th July, 2015. 26. Çengel YA, Kanoğlu M, Boles MA. Gas-vapor mixtures and airconditioning. In: Thermodynamics: an engineering approach. McGraw-Hill Education, 2015:14 27. Stull R. Wet-bulb temperature from relative humidity and air temperature. J Appl Meteor Climatol 2011;50:2267-2269. 28. World climate and temperature. www.climatemps.com. Accessed 24th July, 2015. 29. Florek K, Lukaszewicz J, Perkal J, Steinhaus H, Zubrzycki S. Sur la liaison et la division des points d'un ensemble fini. Colloquium Mathematicum 1951,2:282–285. 30. Sibson R. SLINK: An optimally efficient algorithm for the single-link cluster method. Computer Journal 1973;16:30-34 31. Mojena R. Hierarchical grouping methods and stopping rules - An evaluation. Computer Journal 1977;20:359-363. 32. Milligan GW, Cooper MC. An examination of procedures for determining the number of clusters in a data set. Psychometrika 1985;50:159-179

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33. Nairac A, Townsend N, Carr R, King S, Cowley P, Tarassenko T. A system for the analysis of jet system vibration data. Integrated Computer-Aided Engineering 1999;6:53–65. 34. Mittal A, Kataria T, Das GK, Chatterjee SG. Evaporative Cooling of Water in a Small Vessel under Varying Ambient Humidity. Int J Green Energy 2000;3:347-36. 35. Fisch A, Leblanc H, Cisse H, Pichard E, Zirinis P. Etude de l’altérabilité d’insulines ordinaires dans des conditions climatitiques africaines. Médecine d’Afrique Noire 1987;34:1043-1048. 36. Psychrometric calculator. www.kwangu.com/work/psychrometric.htm. Accessed 29th July 2015. 37. Sarda A. Make your own insulin cooler. www.youtube.com/watch?v=ZtL7c75NNwM. Accessed 29th July 2015.

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9.0 DISCUSSION

9.1 Discussion on Aim 1

Provide the first data on incidence of type 1 diabetes in children in Fiji, Bolivia, and Azerbaijan

Paper 1 determined the incidence of diabetes in children <15 years (y) in the Fiji Islands in the 12-year period from 2001 to 2012. No secondary ascertainment source was available, but given the nature of the inter-relationships within the Fijian health system, and the negative enquiries to the few private doctors who may have seen other patients, we are confident that ascertainment was 100%. Of the 42 new cases of diabetes that occurred in that period, two- thirds (28) were T1D cases. In the childhood population as a whole, the incidence rate was low at 0.93 per 100,000/y year. Age of onset (with mean±SD age of 10.2±2.9 y) and the virtually equal sex ratio were consistent with findings from high-incidence countries. The unusual finding was that the variation in incidence between the predominant indigenous Melanesian/Polynesian population and the Indo-Fijian population (37% of population): the rate/100,000 in indigenous Fijians was 0.23 and in Indo-Fijians was 2.14 (p<0.001). Variable T1D incidence rates in different ethnic populations have been noted in other populations – for instance the United States, where the SEARCH study found rates in children and adolescents age varied substantially between five ethnic groups, with Asians and Pacific Islanders having 5-year age bracket rates up to four times lower than non-Hispanic whites, and American Indians had even lower rates (Writing Group 2007). The low rate in Melanesian/Polynesians are consistent with data from PNG (previously published by myself and colleagues) showing an incidence of 0.1 per 100,000/y (Ogle 2001), with a greater likelihood in that country that some children may die at onset misdiagnosed with another condition, and therefore not be recorded as new cases. New Zealand is another country with a large Polynesian population. Rates in that country’s South Island are 50% higher than the rates in the North Island, and this is largely explained by the lower Maori population on the South Island, as the incidence was 4.5 times higher in Europeans than in Maoris (Campbell-Stokes 2005).The Indo- Fijian incidence is also only a little lower than reported rates from India itself: 3.0 (Kalra 2010, Patterson 2014) and 4.3 (Jensen 2018, Patterson 2019 (DRCP)).

Paper 2 presents a T1D incidence study from Cercado Province in Bolivia. Once again, ascertainment could not be definitively determined, as no secondary ascertainment source was available. However, the government health service does not provide any free care at all for children or adults with diabetes – hospital and clinic visits and every component of care must be paid for by the family. The Centro Vivir con Diabetes clinic provides free care to all in need with diabetes, and it is well-known in the medical and general community for its expertise. Also, the doctors were unaware of any other cases in the area. We estimated ascertainment at 80%, and stated that the uncertainty of this estimate was a limitation. The incidence rate observed (2.2 per 100,000/y, rising to 2.7 when adjusted for ascertainment) is substantially than higher some older published rates from South and Central America in the DiaMond study (for example, 0.1 in Venezuela and 0.5 in Peru (Karvonen 2000,

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DiaMond 2006, Patterson 2019 (DRCP)). Before the publication of Paper 2, the IDF Atlas (Patterson 2014) used the Peru value for Bolivia, which is one-fifth of the adjusted rate in the current study. This rate of 2.7 is still low in a global sense. Some other parts of South America have substantially higher rates – e.g. Uruguay (8.3 in 1992) (Karvonen 2000, Diamond), Chile (12.1 in 2012) (Garfias 2014), and Brazil (10.2 in 2006) (Negrato 2010). A possible contributory reason for this is that Bolivia has, by a substantial margin, the highest proportion of indigenous peoples in Central/South America (Center for Latic American Studies 2020). The lower rates in Amerindians (as also observed in the US SEARCH study (see above), are thought to be due to differing HLA haplotype frequencies (Karvonen 2000, Collado-Mesa 2004, Larenas 1996, Gorodezky 2006, Giraudo Abarca 2014). More Bolivian T1D cases were in females (56.9%), and this is consistent with most other studies in low-incidence countries (Karvonnen 1997). The female preponderance with low incidences is thought to be due to sex differences in the risk of diabetogenic genes when passed on to offspring, combined with young men with T1D possibly being more likely to reproduce than young women with T1D (Karvonen 1997, Tuomilehto 1995, Wäldhor 1995).

Paper 3 presents a T1D incidence data from Azerbaijan. This site was suitable for an incidence study given the nationalised public health system in Azerbaijan, as all cases of diabetes in young people that occur in the capital Baku and the small adjacent province of Absheron have mandatory referral to the 6th Children’s Hospital in Baku. Therefore, ascertainment was estimated as near 100% or full. Azerbaijan has mainly a Turkic population. The observed incidence in children <15 years of 7.05 per 100,000/y was approximately midway between the reported rates in two other Turkic populations – a rate of 10.8 observed in children <18y in Turkey in 2011-13 (Yesilkaya 2017), and a rate of 3.8 <15y that colleagues and I reported in Uzbekistan (Rakhimova 2018).

9.2 Discussion on Aim 2

Investigate the frequency and characteristics of ‘atypical’ forms of type 1 and other causes of diabetes in children and youth in Azerbaijan, Pakistan and Bangladesh (and also Fiji, Bolivia)

The studies in Azerbaijan, Pakistan and Bangladesh have similar methodology, examining clinical presentation, diabetic ketoacidosis (DKA) rates at onset, two diabetes autoantibodies (glutamic acid decarboxylase (GAD-65) and islet cell antigen 2 (IA2)), C-peptide values, and the HLADRB1 gene in approximately 100 new- or recent-onset cases. In Azerbaijan, T1D age of onset (peak age 10 years), autoantibody rates (74% having GAD-65 and/or IA2), fasting C-peptide values (86% <0.13 nmol/L), and predisposing and protective HLA alleles were similar to those in European populations. The onset DKA rate of 58% was higher than most European populations, and presumably due to more frequent delayed diagnosis.

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The findings were substantially different in Pakistan and Bangladesh, where, in those clinically diagnosed with T1D, the age of onset tended to be later (peak age 14 and 12-15 years respectively), DKA rates lower (21.2% and 9.5% respectively), autoantibody rates lower (63.4% and 32.2% respectively having GAD-65 and/or IA2), and C-peptide values in particular were often not low. In Pakistan, DRB1*03:01 was the major and almost exclusive susceptibility allele, which is similar to studies in Somalis (Noble 2017). In Bangladesh, DRB1*04:01 appeared predisposing and DRB1*14:01 appeared protective. Funding restrictions and assay availability limited the number of autoantibodies that could be tested to two, namely GAD-65 and IA-2. It is possible that the addition of zinc transporter-8 autoantibody (ZnT8) and insulin autoantibodies (IA2) may reveal further evidence of autoimmunity. HLA analysis to date has been limited to the DRB-1 gene. (If further funds become available this will be expanded). Also, C-peptide could only be measured on one occasion.

Papers 1-5 also provided new specific information on other types of diabetes in the respective countries. In Fiji, 30.9% of the cases were T2D diagnoses, and again these were more common in Indo-Fijians. It was also noted that there was also an indigenous Fijian child who was diagnosed with T1D at five months of age. Genetic testing at the University of Exeter was arranged. He and an older sibling had a heterozygous INS gene mutation (unfortunately not one of the mutations of the KATP channel that respond to glibenclamide (Hattersley et al.)). In Bolivia, the study only included subjects clinically diagnosed with T1D. However, one child who was diagnosed at three months of age quite possibly has a monogenic form. The partner centre is endeavouring to arrange genetic testing for this child, who lives in a different region of the country. In Azerbaijan, there was one diagnosis of T2D and another of an atypical presentation where insulin was discontinued after three months and the child was managed with glimepiride. All 100 cases in Pakistan were diagnosed with T1D. This may have partly represented selection bias. Nine cases (9.0%) in Bangladesh had fibrocalculous pancreatic disease (confirmed by pancreatic calcification on ultrasound or X-ray). These cases are clearly distinct, and yet three of these had at least one autoantibody. Seven cases were diagnosed as T2D (one of who was positive for IA2 alone). It is possible that further testing and follow-up of some of the subjects in Pakistan and Bangladesh who were autoantibody negative and did not have low C-peptide values would indicate that they were clearly a T2D diagnosis.

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9.3 Discussion on Aim 3

Document factors hindering access to type 1 diabetes care for young people in less-resourced countries, and propose an “intermediate” care level suitable for such countries.

The “Index of diabetes care for children and youth” study (Paper 6) clearly shows that provision of care for children and youth with T1D in less-resourced countries is deficient, not just in the area of insulin, but also involves limited access to virtually all components of care. The inclusion of data from 20 high-income and 14 upper-middle income countries strengthened the study by showing the clear contrast with well-resourced health systems. Indeed, provision of insulin, although often poor, was better than provision of SMBG supplies and particularly of glucagon injections for the treatment of severe hypoglycaemia, (which was not available to even 5% of the T1D population in any low- or lower-middle income country). The study also showed that access to skilled health professionals, education resources, 24-hour emergency phone support, diabetes camps, and some other components of care was also less in lower-income countries. The overall index score for a particular country was strongly related to per capita Gross Domestic Product (R2=0.77, p<0.001) and Health Expenditure (R2=0.77, p<0.001). The United Nations and all member states have agreed on the goal of Universal Health Coverage (UN General Assembly 2015). Paper 7 is a unique study of progress towards Universal Health Coverage for insulin and blood glucose meters and strips. Four domains were assessed in 44 countries: three (population covered, services provided, and direct costs), according to the WHO “Fair Choices” cube (WHO 2014), and a fourth estimating availability. Key findings included: i) that there were many countries where the public health system did not provide insulin, but even more that did not provide blood glucose meters and strips (as was found by different methods in Paper 6), and ii) that national health insurance schemes were helping to address access issues in some countries, but some of these schemes were only available to families with a reasonable income, potentially exacerbating inequalities.

In the many lower-income countries where governments cannot provide the needed components of care, families must purchase the supplies themselves unless there is some charitable support. Paper 8 documents such costs for families for insulin, blood glucose meters and strips, and HbA1c testing in 15 countries. Key findings were: i) that provision of even two blood glucose strips per day was more expensive that insulin in most of the countries where neither were provided by the government; ii) that the cost of even basic supplies (human insulin, two syringes per week, two blood glucose strips per day, and quarterly HbA1c testing) exceeded the average annual income in some countries; and iii) that India had the lowest costs for supplies, presumably due to its large market increasing competition, and its local manufacturers of insulin.

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Paper 9 is a unique review of issues surrounding global access to blood glucose meters and strips, which are used for SMBG in people with diabetes and also in various clinical settings. With the support of data from the health information company IQVIA (Durham, US), the paper was able to provide much previously unpublished information on test strip numbers sold and their cost, although available information was scant from less-resourced countries. Key findings were: i) the market is dominated by four companies, but a number of smaller providers supply 15.0% of the global market, which raises hopes that competition could bring prices down further; ii) competitive bidding such as done by New Zealand could be a very effective method for countries to reduce purchase costs; and iii) many countries imposed substantial customs and duties, higher than those for medicines, as SMBG supplies are categorised as medical devices rather than medicines. The paper also made various recommendations for international and national approaches. Appropriate treatment of T1D is outlined in the Consensus Guidelines of the International Society for Pediatric and Adolescent Diabetes (ISPAD) (ISPAD 2018). The above findings show that this is not being provided in many low-income countries. Expecting such countries to provide the ‘Comprehensive Care’ detailed in the ISPAD guidelines is unrealistic due to its cost. However, current government provision in many countries results in high mortality and morbidity (Sidibe, Atun), and this is unacceptable. Given this, I, with the help of Trevor Orchard, Ragnar Hanas, Julia von Oettingen and Angela Middlehurst, developed a concept of ‘Levels of Care’ for T1D in young people (paper 10). Comprehensive (Guidelines-based) Care should be the goal for public health systems everywhere, but is unrealistic in lower-income countries. ‘Minimal Care’, with barely enough insulin to stay alive, minimal blood glucose monitoring, and virtually no diabetes education results in poor outcomes. We proposed a concept of ‘Intermediate Care’, which includes human insulin (preferably administered in a ‘basal-bolus’ regimen), along with at least two blood glucose tests per day, quarterly HbA1c testing, appropriate diabetes education, and basic screening for diabetes complications. This ‘Intermediate Care” level should be achievable in all less-resourced countries, if necessary with the support of international groups such as Life for a Child (which aims to support this care model). The Bolivia study (Paper 2) shows that ‘Intermediate Care’ can achieve the reasonable outcomes proposed in Paper 10. The results were a mean HbA1c of 8.5% (69 mmol/mol) and median of 8.2% (66 mmol/mol). These are outcomes similar to those of the T1D Exchange in the United States (a collaboration of 76 leading US centres) (Miller 2015). In another study (Mota- Orepeza 2019), Mexican and Australian colleagues and I have documented similar results from Mexico (8.7%/72 mmol/mol and 8.4%/68mol/mol respectively), and with Indian and US colleagues a mean of 8.3% (67 mmol/mol) (Gupta 2016) in India. It should be noted that some of the patients in the Bolivian, Mexican and Indian studies were receiving insulin analogues. (Insulin analogues are modifications on the human insulin molecule engineered in laboratories,

189 to increase or to prolong activity with the aim of improving glycaemia, and are more expensive than human insulin).

9.4 Discussion on Aim 4

Determine the efficacy of traditional and modern evaporative cooling devices in reducing insulin storage temperatures.

The study found that all 13 devices from seven less-resourced countries, along with a proprietary manufactured device from the U.K., reduced storage temperature, but some were more efficacious than others. This was a novel study in various respects. No previous study had looked at more than one device, nor had any studied a proprietary manufactured device. Secondly, we were also able to use an electronic monitor that permitted temperature readings every 5-minutes for the whole study period of two periods of 44 hours. Thirdly, appropriate consideration was given to humidity, which had not been discussed at all in the limited previous studies. The amount of evaporative cooling that is theoretical possible in any situation is largely dependent upon the relative humidity - at 100% humidity, no cooling can occur. As humidity falls more cooling becomes possible. There is a limit to the amount of cooling that occurs – the ‘wet-bulb temperature’ – which is a function of the ambient temperature and the relative humidity level. The current study developed a metric for the amount of cooling achieved, which we termed the ‘relative cooling effect’. This was calculated as follows: Relative cooling effect (expressed as a %) = (ambient temperature – achieved internal device temperature) / (maximum cooling effect). The maximum cooling effect is the difference between the ambient temperature and the wet bulb temperature.

The relative cooling effect of the devices ranged from 71.3±5.3% to 29.8±1.3%. The cooling occurred at all times of the day and night. Some devices were markedly more efficacious than others. Some variation was predictable – the open bucket of wet sand and the relatively impermeable vegetable gourd performed poorly, with larger devices tending to do better. It was encouraging to find that the proprietary manufactured cooling wallet (the FRIO™ cooling wallets), performed no better on cluster analysis that three traditional devices, and furthermore, this was only when the manufactured device was suspended in air. When laid flat, the results from the cooling wallet were in the second level of efficacy group on cluster analysis. The surprise entrant was the suspended goat skin filled with water. This performed in the top efficacy group on cluster analysis, and indeed had the highest relative cooling effect of any device (presumably due to its large evaporative area). This is a further demonstration of local ingenuity in the face of the challenge of lack of refrigeration. We also developed an approach whereby the potential utility of a clay pot or other device in any particular location could be predicted. The formula predicts the achieved internal device temperature based on: the ambient temperature and relative humidity (available from local weather records), the calculated wet bulb temperature (available from an online psychrometric calculator), and an estimate of relative cooling effect (e.g. 62.8% being an average

190 of the eight most efficacious devices (the top two clusters). This approach, combined with the limited published information on insulin thermostability beyond room temperature, was used to show that these devices may not be needed at all in some more temperate regions in Africa, and also that they may have a more limited effect in regions where hot temperatures are associated with high humidity.

Overall, this set of 11 papers has various strengths and limitations.

The strengths include: a) The novelty of the work (there having been no previous published information on diabetes in young people from Bolivia or Fiji, and very limited information from Azerbaijan, Pakistan and Bangladesh) b) The capacity building that resulted in these countries from the involvement in research of parameters that had not been studied in this context (such as HLA, C-peptide and autoantibodies) c) Data from over 40 less-resourced countries on organisation of care and costs of care d) Detailed delineation and assessment of the previously very limited coverage of the issue of supplies for self-monitoring of blood glucose e) New approaches and frameworks such as the Index, progress towards Universal Health Coverage, and efficacy of insulin storage devices.

The limitations include: a) The lack of certainty of the degree of ascertainment of incidence due to only one source being available in each country b) The inability to perform further characterisation on the atypical forms of T1D seen in Pakistan and Bangladesh, due to resource constraints c) The fact that the surveys on organisation of care, costs of care, and progress towards Universal Health Coverage were generally limited to one informant per country, albeit the person that we had previously recognised as the most expert in the field.

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10.0 SUMMARY AND FUTURE DIRECTIONS

10.1 Incidence

Papers 1-3 determined T1D incidence rates in three countries that had no prior information (Fiji, Bolivia and Azerbaijan). These data have been included in the 2019 IDF Atlas (IDF 2019), and used to derive estimates of prevalence and mortality as well (Patterson 2019 (IDF)). In the absence of local data, the Atlas now also uses the rate for Azerbaijan for Tajikistan and Afghanistan, and the Fiji rate is being used for seven other Pacific island nations. The ‘gold-standard’ in T1D incidence studies is to have two or more independent but strong sources of data, and then to use the ‘capture-recapture’ statistical method to determine incidence (La Porte 1985, DiaMond 2006). A challenge is that secondary, let alone tertiary sources, are not available at all in most less-resourced countries. If multiple independent sources are seen as essential, there would be almost no data at all from such countries, which does not advance knowledge and clinical practice. Other challenges for conducting incidence studies in less-resourced countries include the presence of multiple care providers (particularly if many are in the private sector, such as in India), difficulties with tracking cases that are lost to follow-up due to challenges with communications and logistics, determining exact dates of birth, the possibility that incidence may be underestimated if there are deaths at onset from misdiagnosis (which is thought to be common in some countries (Rwiza 1986, Makani 2003, Atun 2017, Marshall 2013, Paper 6), and the diagnostic uncertainty discussed in Aim 2 of this thesis. These three studies demonstrate that, despite these challenges, incidence studies can be done in some less-resourced countries. It is crucial that the whole country/region to be studied is selected after careful consideration of health system structure and referral practices, to ensure that ascertainment is as complete as possible. In two studies (Fiji and Azerbaijan), we are confident of 100% or near-100% ascertainment. In Bolivia ascertainment was estimated at 80%. It is quite possible it is lower or higher than that figure. However, I propose that knowledge of even a ‘minimum incidence’, with clearly stated limitations, is still very helpful, and much better than no data at all. In Bolivia, even the ‘minimum incidence’ estimate was over four times the previously estimated figure. There is a need for more incidence studies in lower-income countries. It is also important that as many studies as possible are ongoing, so that it can be determined if the incidence is rising, and if so at what rate. Globally, incidence has been rising by about 3% (DiaMond 2006, Patterson 2014, Patterson 2019 (Diabetologia). However, there is evidence that rates of increase are higher in lower-income countries where Gross Domestic Product (GDP) is increasing rapidly (Gomez-Lopera 2019), and an unpublished analysis that Jayanthi Maniam and I have performed of data from 22 European nations reported in Patterson et al. (2019 (Diabetologia)) showed that the rate of increase was correlated to GDP (R2 = 0.275, p = 0.012). Finally, my colleagues and I have also reported annualised high rates of increase of T1D incidence of in Uzbekistan (5.6% per year from 1998-2014) (Rakhimova 2018) and Maldives 12.0% from 2009-2018 (Majeed 2020).

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Incidence data are important for all countries to guide planning of care, but from a global perspective it is critical to have recent data that has a high certainty of degree of ascertainment from lower-income countries with high populations, such as India, Indonesia, Pakistan, Nigeria, Bangladesh, Mexico, Ethiopia, Philippines, and Egypt. Life for a Child is already working with in-country partners in some of these countries, aiming to meet this need. I have also been asked by the International Diabetes Federation Atlas Committee (and have agreed) to participate in the development of Guidelines aimed to increase the numbers of countries with current sound data on incidence and prevalence. Also, I have guided the development a novel Markov model that predicts incidence, prevalence and mortality under various scenarios. (The model was developed for Life for a Child by Gabriel Gregory, a University of Sydney medical student). This model is being used to determine how many young people with diabetes “should be” alive in a particular country, if mortality was at the level of that observed in high-income countries. It has recently been expanded and made more statistically robust as part of the JDRF/LFAC/IDF/ISPAD “Type 1 Diabetes Index” Project, which will be released in 2021.

10.2 Types of diabetes

Papers 2 and 3 showed that ‘atypical’ forms of T1D were common in the populations studied in Pakistan and Bangladesh, with concomitant substantial difficulty in delineating T1D from T2D. This is consistent with previous results from Bangladesh (Zabeen 2013), Pakistan (Fatima 2013) and India (Balasubramanian 2003, Singh 2000, Goswami 2001, Tandon 2002, Dayal 2015). We have also conducted similar studies to those in Azerbaijan, Pakistan and Bangladesh in three other countries – Sudan, Mali and Haiti. These have been presented in abstract form (Ogle 2017) and manuscripts are currently being prepared for submission, likely in 2020. Key preliminary findings are that atypical cases were also common in Mali and Haiti, whilst Sudan had more classic findings. HLA patterns were also different from European populations, with Sudan showing a DRB1*03:01 association, as was seen in the Pakistan study. It is important to determine if addition of the two autoantibodies we could not measure - insulin autoantibody and ZnT8 – increases the rates of autoimmunity in cases that present clinically as T1D. There is some evidence from India that ZnT8 positivity can occur in cases without GAD-65 or IA2 titres being elevated (Shivaprasad 2014). The Barbara Davis Center in Denver has developed a dried-blood assay for all four autoantibodies (Simmons 2016). Studies using this method have just been conducted at LFAC centres in Maldives, Pakistan and Bangladesh, and results are currently being analysed. Ethics approval is being pursued for studies in Tanzania, Nepal, and Ethiopia. It is likely that further analysis of non-DRB1 HLA genes in the studied countries and other non-European populations will reveal further haplotypes that induce susceptibility or protection to development of T1D in these populations, as they do in predominately European populations (Mayer-Davis 2018, Katsarou 2017). Other genes also play an albeit lesser role in susceptibility to T1D in European populations, and presumably these could vary in non-European populations.

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Such investigations are becoming more accessible with development of gene array tests, such as the Type 1 Genetic Risk Score developed by the University of Exeter (Oram 2016). The studies presented in this thesis all only measured fasting C-peptide levels on one occasion, and this was not always at diabetes onset, but sometimes in the ‘honeymoon period” or afterwards. A longitudinal study that measures C-peptide at diagnosis and then every six months out to three years duration or more would give more information, as may indirect or direct measurement of stimulated C-peptide (Buchanan 2019). Also, measurement of insulin sensitivity would be likely to provide substantial new information and may also guide the use of insulin sensitising drugs, such as metformin, in a subset of patients. It is very likely that this ‘atypical’ group is itself a heterogenous group with varying degrees of insulin deficiency and resistance.

10.3 Access to care

Papers 6-10 clearly show that many components of diabetes care need to be addressed to broadly improve care in less-resourced countries. A holistic approach is needed: attention must be given not only to insulin but also to other supplies (syringes, glucose meters and strips, glucagon), HbA1c testing, health professional skills, diabetes education, and complications screening. Life for a Child is disseminating the Paper 10 concept of ‘Intermediate Care’, with the aim to support advocacy efforts of in-country partner to their respective governments. It is straightforward to develop a moral argument that these young people deserve appropriate care, as otherwise they will die. It would be useful to have an economic argument to accompany this: i.e. that it is not only a moral issue but it is also cost-effective to the society due to the prevention of later costs of complications and lost productivity. Recently, I have been able to lead a collaboration to assess the cost-effectiveness and impact of ‘Intermediate Care’ versus “Minimal Care’. This health economics study used 30-year complications data from the Epidemiology of Diabetes Complications (EDC) study of the University of Pittsburgh (provided by Professor Trevor Orchard and Dr Jingchuan Guo), and cost data from six countries (Azerbaijan, Bolivia, Mali, Pakistan, Sri Lanka and Tanzania). These data were fed into a second mathematical model (similar to that mentioned in 10.1 above) to determine outcomes and costs over 30 years. This study has just been published in Pediatric Diabetes (Gregory 2020), and shows that ‘Intermediate Care” is cost-effective and results in marked reductions in serious diabetes complications and mortality. These results will be used by national diabetes associations and other advocates to advocate for improvements in government care provision, and the modelling is being extended to other countries. The methodology established in the Index paper (Paper 6) and the Universal Health Coverage paper (Paper 7) can readily be repeated in a few years to document the extent of progress (or retreat if national health budgets have been impacted by the COVID-19 pandemic). Paper 10 also lays out the reasons why human rather than analogue insulins are preferable choices for a less-resourced health system. Analogue insulins are much more costly, and definitive benefits are limited to a reduction in severe nocturnal hypoglycaemia (Davidson 2014). Likewise, although insulin injection by an insulin pen or pump is preferable, injection by

194 needle and syringe using vial insulin is less expensive and therefore also preferable where there are limited funds. The most promising ‘new’ development for less-resourced situations is continuous glucose monitoring (CGM), measuring interstitial fluid glucose. There is strong evidence that frequency of SMBG is directly related to reduction in HbA1c (e.g. Miller 2013), and that this is further improved by CGM (DiMeglio 2018, American Diabetes Association 2020). CGM devices also provide extra useful information such as time-in-range, time-in- hypoglycaemia, data on glycaemic variation (DiMeglio 2018, American Diabetes Association 2020). Until recently the cost of available CGM devices has been very high. However, the development of the Libre Freestyle system by Abbott (Evans 2020) raises hope that less- expensive devices will soon be available. With smartphone access also increasing globally, as well as complementary apps that inform both the person with diabetes and the health professional of the CGM data, it is possible to conceive of a quantum leap straight from minimal/no blood glucose monitoring to a full, immediate, and actionable knowledge of interstitial fluid glucose levels (which reflect blood glucose levels). This is already possible in high-income settings. Studies using such devices are indicated in less-resourced countries. Finally, as usage of CGM devices becomes more common and thereby largely replace meters and strips in resourced situations, it is imperative that blood glucose meters and strips remain in production and affordable on the international market. These studies show that, for people with T1D in less-resourced countries, access to and cost of SMBG can be a greater problem than that for insulin. Paper 9 offers various recommendations to improve this, including international attention to reducing customs and duties on medical devices, use of competitive bidding, and development of a robust and accurate low-cost testing system suitable for use in less-resourced situations. Education is critical on various levels for T1D care in young people. Firstly, doctors and nurses need to have the knowledge and mentoring to properly manage this complex disorder. Life for a Child and ISPAD have developed ‘Pocketbook Guidelines’ (Life for a Child, 2017) which are a simplified version of the ISPAD Consensus Guidelines (ISPAD 2018) and these have been translated into various languages and widely distributed. The Paediatric Training Colleges in Nairobi and Lagos are training young African paediatric endocrinologists (Odundo 2016). Training/mentoring visits by thoughtful, flexible and experienced doctors and nurses from high- income countries could also help training in receptive centres. On-line education is also possible, and a program has been commenced by the European Society for Paediatric Endocrinology (ESPE 2020). The international professional T1D community should consider how to increase such efforts, and at the same time evaluate them to optimise impact. Secondly with respect to education, families and the young people themselves need to understand T1D and then learn how to adjust their insulin dosages and blood glucose testing routines to changing circumstances of food intake, exercise and other daily events. Education materials that are age-, language- and culture-specific are needed, with more visual materials especially needed for those with limited formal education. The Changing Diabetes in Children Program has excellent patient education materials available in some languages (CDiC 2020) and these should be made more available and translated into further languages. The Moseka graphic novel (first developed in the Democratic Republic of Congo) and the Professor Bumblebee video have been very popular and widely translated (LFAC 2020), but further novel, imaginative, and

195 visual resources are needed in a number of areas, including such areas as: what is T1D?, how to administer injections, how to adjust insulin doses, and carbohydrate counting. Systematic data collection and analysis of any particular centre’s outcomes helps identify strengths and weaknesses and allows comparison with centres in similar situations. The concept of benchmarking has been introduced into paediatric diabetes care by the European- based Hvidoere group (de Beaufort 2009, Cameron 2013), and taken further by the international SWEET Project (Pacaud 2016, Witsch 2016). As many centres as possible should be encouraged and facilitated to join the SWEET initiative. Other areas that are currently under-investigated in less-resourced settings are listed in Table 1 below:

Table 1: Other access to care areas that warrant further study/attention

Access to insulin delivery devices Access to low-cost thermostable glucagon and ketone strips Access to HbA1c testing Development of a global access program that enables measurement of diabetes autoantibodies and other immune markers, C-peptide and relevant genes, possibly through filter-paper collection or other lower-tech collection methods Task-shifting (with respect to health professionals) in T1D care – current situation in different world regions, successes and challenges, and possibilities for expansion Prevention and early treatment of diabetic nephropathy and retinopathy Minimisation of concurrent cardiovascular risk factors through more thorough routine screening, as well as education and early intervention Management and support in situations of extreme poverty and food insecurity Identification of population subsets that may be at higher risk of mortality – e.g. those distant from care, followed by implementation of supportive measures The value of peer-support and on-line social networks e-learning and e-mentoring for health professionals Documenting and improving pregnancy outcomes in young women with T1D Use of human rights principles and agreements to support advocacy efforts

10.4 Insulin storage

Paper 11 – the ‘Clay Pot Study’ clearly demonstrated that traditional evaporative cooling devices are efficacious in reducing insulin storage temperatures, achieving temperatures close to room temperature in many situations. Wide dissemination of these results by Life for a Child and others has reassured health professionals in many countries that these devices are efficacious, and in turn they have been able to encourage families who are concerned about the product guidelines on insulin storage. The results also showed which devices were more effective, with suggestions as to why this may be so (e.g. permeability, evaporative area).

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The study developed a novel approach to measuring the efficacy of a device, and also predicting the efficacy of a device in a particular climate. The study could easily be replicated at minimal cost by others if they wished to assess devices in any particular location. The important information that is still unknown is the thermostability of currently used insulin preparations when stored for longer than one month at temperatures slightly or markedly higher than room temperatures. Studies on animal insulin in the 1960’s and 1970’s showed that potency was preserved for a long time with modest elevations of temperature, as the exponential decline in potency was modest with small temperature elevations (Storvik 1968, Pingel 1972, Brange 1987). However, despite calls for this information, there are no comparable published data for human or analogue insulin, with only the manufacturer’s recommended storage information on maximum temperature and maximum period outside refrigeration available, (Grajower 2003, Gallo 2004, Molitch 2004, Grajower 2014, Keller 2003). There is a need for companies to release these data. In my role with the Life for a Child Program, I have advocated for this information through the International Diabetes Federation and by direct approach to manufacturers, and also we contributed to the Boston Declaration of the ‘Diabetes in Humanitarian Crises” Group, which has this issue included in the priority agenda for action (Kehlenbrink 2019). Aside from the insulin manufacturing companies releasing more information from their internal data, this issue is now being studied by a group based at the University of Florida (USA), and another at the University of Gothenburg (Sweden) (Malmodin 2019). I was asked to advise in the initial planning of the University of Florida study, and have been approached by Gothenburg group to help develop a real-world study to test the potency of insulin stored in and out of evaporative cooling devices. This study is now being planned, and the University of Florida will participate as well. The two groups are assessing insulin potency with different methods – the US team use HPLC (High-Performance Liquid Chromatography), and the Swedish group are using NMR (Nuclear Magnetic Resonance) Spectroscopy. Finally, the development of an affordable thermostable insulin, which is underway, would solve the problem completely.

In conclusion, this series of clinical studies of diabetes in children and youth in less- resourced countries has achieved the overall goal of providing new data to improve understanding of diabetes in these populations. The studies have laid a solid foundation for ongoing clinical research and advocacy that will guide future diabetes diagnosis and care to improve health outcomes for these vulnerable young people. The year 2021 marks the centenary of the discovery of insulin, and yet it and other components of care are still not available to many who need it. For these young and older people, tailored, coordinated efforts by the international diabetes community, combined with public health services initiatives and technological advancements, have the potential to telescope 100 years of advancement in diabetes care into just a few years.

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12.0 APPENDICES

Appendix A: PDFs of published papers.

Paper 1 pp 207-211 Paper 2 pp 212-219 Paper 3 pp 220-227 Paper 4 pp 228-236 Paper 5 pp 237-244 Paper 6 pp 245-255 Paper 7 pp 256-266 Paper 8 pp 267-273 Paper 9 + Appendix pp 274-291 Paper 10 pp 292-297 Paper 11 pp 298-307

This material has been removed by the author of this thesis for copyright reasons.

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Minerva Access is the Institutional Repository of The University of Melbourne

Author/s: Ogle, Graham David

Title: Context for improving access to care for children and youth with diabetes in less-resourced countries

Date: 2020

Persistent Link: http://hdl.handle.net/11343/258621

File Description: Redacted thesis file

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