IDF Diabetes Atlas
Global estimates of undiagnosed diabetes in adults

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Abstract

Aims

The prevalence of diabetes is rapidly increasing worldwide. Type 2 diabetes may remain undetected for many years, leading to severe complications and healthcare costs. This paper provides estimates of the prevalence of undiagnosed diabetes mellitus (UDM), using available data from high quality representative population-based sources.

Methods

Data sources reporting both diagnosed and previously undiagnosed diabetes were identified and selected according to previously described IDF methodology for diabetes in adults (aged 20–79). Countries were divided into 15 data regions based on their geographic IDF Region and World Bank income classification. The median UDM proportion was calculated from selected data sources for each of data region. The number of UDM cases in 2013 was calculated from country, age and sex-specific estimates of known diabetes cases and data region-specific UDM proportion.

Results

Of 744 reviewed data sources, 88 sources representing 74 countries had sufficient information and were selected for generation of estimates of UDM. Globally, 45.8%, or 174.8 million of all diabetes cases in adults are estimated to be undiagnosed, ranging from 24.1% to 75.1% across data regions. An estimated 83.8% of all cases of UDM are in low- and middle-income countries. At a country level, Pacific Island nations have the highest prevalence of UDM.

Conclusions

There is a high proportion of UDM globally, and especially in developing countries. Further high-quality studies of UDM are needed to strengthen future estimates.

Introduction

The number and prevalence of people with diabetes is rapidly increasing [1]. The International Diabetes Federation (IDF) estimates that there are 381.8 million people with diabetes in 2013 with a projected increase of 55% to 591.9 million by 2035 [1]. As a result of a combination a number of factors including: under-performing health systems, low awareness among the general public and health professionals, and the often slow onset of symptoms or progression of type 2 diabetes, the condition may remain undetected for many years, during which time complications may develop. Population-based studies actively screening for diabetes using either oral glucose tolerance test (OGTT) or fasting blood glucose provide the backbone for estimating undiagnosed diabetes (UDM). In such studies, participants who report not having been diagnosed with diabetes may be found to have diabetes upon testing of their blood glucose and would therefore be classified as having UDM, i.e., ‘previously undiagnosed’ or ‘newly diagnosed’ diabetes. While it is possible to have undiagnosed type 1 diabetes, this is usually short in duration due to the rapid onset of symptoms, and would not likely be measured in the population-based studies necessary for the estimation of undiagnosed diabetes. However, few studies reporting the prevalence of diabetes make a distinction between type 1 and type 2 diabetes, and it is therefore not possible to separate any estimate of undiagnosed diabetes.

The prolonged asymptomatic phase of type 2 diabetes may last many years [2], during which time unmanaged elevated blood glucose leads to serious and irreversible development of micro- and macrovascular complications including neuropathy, nephropathy, retinopathy, coronary artery disease, stroke and peripheral vascular disease [3], [4]. Rates of complications have been shown to be high in people with UDM compared to normoglycaemic individuals. In the USA, up to 41.7% of adults with previously undiagnosed diabetes have chronic kidney disease [5]. The prevalence of some level of diabetic retinopathy among individuals with UDM in China is over 30% [6], and a recent review found the prevalence of diabetic retinopathy to exceed 15% in one third of all populations investigated [7]. Furthermore, BMI, blood pressure, and other cardiovascular and metabolic markers have been found to be significantly higher in a cohort of people with coronary artery disease and also UDM compared with diagnosed diabetes; likely due to awareness of the condition and subsequent dietary modifications [8]. Undiagnosed diabetes has been reported to carry a similar risk of mortality to diagnosed diabetes, and is associated with a 1.5- to 3.0-fold higher risk of mortality compared to normoglycaemic individuals [9], [10].

Without the mechanisms and resources necessary for early detection, a person with diabetes may only be diagnosed after the onset of complications. Prevention of complications in people with diabetes by timely lifestyle and pharmaceutical interventions has been shown to reduce hyperglycaemia and risk of complications, [11], [12], [13] but this potential benefit is lost in people with UDM [14]. In addition to a heavy health burden, the financial costs of diabetes-related health expenditures weigh heavily on individuals, health systems and governments, with global health expenditure estimated to be at least 548.5 billion USD in 2013 [15]. The cost of undiagnosed diabetes may contribute substantially to this estimate. One study from the USA found that an additional 2864 USD were spent on direct and indirect costs per person with UDM per year, or 18 billion USD nationally [16]. While the cost of screening for and subsequently treating diabetes is considerable, it is far outweighed by the cost of treating potentially preventable diabetes-related complications [17], [18]. It is important to produce regional and global estimates of UDM in order to understand the burden of UDM globally and regionally, its drivers and potential implications for policy and practice.

While the existence of UDM has long been recognised [19], wide-reaching awareness among the general public, physicians and policy-makers is lacking and there are limited reliable and comparable data available on the subject. Nationally representative population-based studies using OGTT are considered the gold standard for studying the prevalence of diabetes and quantifying undiagnosed diabetes [19]. However, the availability of these studies is varied and may be limited for similar reasons to those which cause diabetes to go undiagnosed; namely that screening effectively for diabetes is costly, time consuming, and, for many countries, not a priority. However these considerations should be balanced by the costs and health burden associated with UDM.

IDF first produced estimates of UDM in 2011 [20], providing a global-scale quantification of this burden. An accurate estimation of the burden of UDM is highly relevant given the high health-related and financial costs associated with diabetes.

Given the lack of awareness and considerable burden of UDM, this paper presents a standardised method and accompanying results for country, regional and global estimates of UDM for the year 2013. These estimates are included in the 6th edition of the IDF Diabetes Atlas [15].

Section snippets

Literature review and selection of data sources

The IDF methodology for estimating diabetes prevalence has previously been described and updated [1], [21] and is summarised in Fig. 1. Briefly, data sources reporting the prevalence of diabetes were identified through a systematic literature search for the period November 2010–June 2013, using PubMed, Google Scholar, websites of governments, the World Health Organization and associated organisations, personal communication with investigators in the IDF network, and by searching reference lists.

Literature search

Of the 744 reviewed data sources, 174 were used for diabetes prevalence estimates in adults (20–79 years); 88 sources with information on known and previously undiagnosed diabetes were selected (Fig. 1, Appendix).

Table 1 presents the UDM proportion by data region, including study characteristics and range of data that contributed to the regional estimate. Overall, data were drawn from 74 of 219 countries (33.8%). Middle-income countries had the highest proportion of countries represented by

Discussion

Globally, 174.8 million people are estimated to have UDM using the standardised IDF methodology described in this paper. These estimates confirm that lack of detection of diabetes persists throughout the world, across all regions and income groups. Despite a variation in availability and quality of data, studies were available for every IDF Region and all income groups (Table 1).

While there is wide variability in the proportions of UDM from the underlying sources for the AFR-LIC region (Table 1

Limitations

The principal limitation in generating accurate estimates for UDM is the lack of high quality data suitable for inclusion. Given that the data regions with sparse data sources tend to be those comprised of LICs and MICs, consideration should be given to how these countries could be supported. Many countries invest in large scale studies, but base these on self-reported data, or may either not record whether subjects had previously been diagnosed with diabetes before screening, or not report

Conclusion

The results of this global study confirm the alarmingly high proportions of UDM in many areas of the world. Undiagnosed diabetes is harmful and costly; both financially and in terms of complications for individuals, communities, and health systems. Nonetheless, it is imperative that the response to these data should be appropriate to the varying capacities of national health systems. Even in countries with the most developed health systems, the proportion of patients not achieving target

Conflict of interest

The authors declare that they have no potential conflict of interest, including specific financial interests, relevant to the subject of this manuscript.

Funding

The 6th edition of the IDF Diabetes Atlas was supported by the following sponsors: Lilly Diabetes, Merck and Co, Inc., Novo Nordisk A/S supported through an unrestricted grant by the Novo Nordisk Changing Diabetes® initiative, Pfizer, Inc., and Sanofi Diabetes.

Acknowledgements

With many thanks to Dr Lydia Makaroff for carefully reviewing this manuscript, and to the IDF Diabetes Atlas Committee, and in particular Dr David Whiting, Professor Jonathan Shaw and Professor Ian Hambleton for their assistance and expertise in developing the estimates.

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