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      Cost of diabetes mellitus in Africa: a systematic review of existing literature

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          Abstract

          Background

          There is an increasing recognition that non communicable diseases impose large economic costs on households, societies and nations. However, not much is known about the magnitude of diabetes expenditure in African countries and to the best of our knowledge no systematic assessment of the literature on diabetes costs in Africa has been conducted. The aim of this paper is to capture the evidence on the cost of diabetes in Africa, review the methods used to calculate costs and identify areas for future research.

          Methods

          A desk search was conducted in Pubmed, Medline, Embase, and Science direct as well as through other databases, namely Google Scholar. The following eligibility criteria were used: peer reviewed English articles published between 2006 and 2016, articles that reported original research findings on the cost of illness in diabetes, and studies that covered at least one African country. Information was extracted using two data extraction sheets and results organized in tables. Costs presented in the studies under review are converted to 2015 international dollars prices (I$).

          Results

          Twenty six articles are included in this review. Annual national direct costs of diabetes differed between countries and ranged from I$3.5 billion to I$4.5 billion per annum. Indirect costs per patient were generally higher than the direct costs per patient of diabetes. Outpatient costs varied by study design, data source, perspective and healthcare cost categories included in the total costs calculation. The most commonly included healthcare items were drug costs, followed by diagnostic costs, medical supply or disposable costs and consultation costs. In studies that reported both drug costs and total costs, drug costs took a significant portion of the total costs per patient. The highest burden due to the costs associated with diabetes was reported in individuals within the low income group.

          Conclusion

          Estimation of the costs associated with diabetes is crucial to make progress towards meeting the targets laid out in Sustainable Development Goal 3 set for 2030. The studies included in this review show that the presence of diabetes leads to elevated costs of treatment which further increase in the presence of complications. The cost of drugs generally contributed the most to total direct costs of treatment. Various methods are used in the estimation of diabetes healthcare costs and the costs estimated between countries differ significantly. There is room to improve transparency and make the methodologies used standard in order to allow for cost comparisons across studies.

          Electronic supplementary material

          The online version of this article (10.1186/s12992-017-0318-5) contains supplementary material, which is available to authorized users.

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          Most cited references 47

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          Diabetes in sub-Saharan Africa.

          In Sub-Saharan Africa, prevalence and burden of type 2 diabetes are rising quickly. Rapid uncontrolled urbanisation and major changes in lifestyle could be driving this epidemic. The increase presents a substantial public health and socioeconomic burden in the face of scarce resources. Some types of diabetes arise at younger ages in African than in European populations. Ketosis-prone atypical diabetes is mostly recorded in people of African origin, but its epidemiology is not understood fully because data for pathogenesis and subtypes of diabetes in sub-Saharan African communities are scarce. The rate of undiagnosed diabetes is high in most countries of sub-Saharan Africa, and individuals who are unaware they have the disorder are at very high risk of chronic complications. Therefore, the rate of diabetes-related morbidity and mortality in this region could grow substantially. A multisectoral approach to diabetes control and care is vital for expansion of socioculturally appropriate diabetes programmes in sub-Saharan African countries. Copyright 2010 Elsevier Ltd. All rights reserved.
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            Diabetes in Sub Saharan Africa 1999-2011: Epidemiology and public health implications. a systematic review

            Background Diabetes prevalence is increasing globally, and Sub-Saharan Africa is no exception. With diverse health challenges, health authorities in Sub-Saharan Africa and international donors need robust data on the epidemiology and impact of diabetes in order to plan and prioritise their health programmes. This paper aims to provide a comprehensive and up-to-date review of the epidemiological trends and public health implications of diabetes in Sub-Saharan Africa. Methods We conducted a systematic literature review of papers published on diabetes in Sub-Saharan Africa 1999-March 2011, providing data on diabetes prevalence, outcomes (chronic complications, infections, and mortality), access to diagnosis and care and economic impact. Results Type 2 diabetes accounts for well over 90% of diabetes in Sub-Saharan Africa, and population prevalence proportions ranged from 1% in rural Uganda to 12% in urban Kenya. Reported type 1 diabetes prevalence was low and ranged from 4 per 100,000 in Mozambique to 12 per 100,000 in Zambia. Gestational diabetes prevalence varied from 0% in Tanzania to 9% in Ethiopia. Proportions of patients with diabetic complications ranged from 7-63% for retinopathy, 27-66% for neuropathy, and 10-83% for microalbuminuria. Diabetes is likely to increase the risk of several important infections in the region, including tuberculosis, pneumonia and sepsis. Meanwhile, antiviral treatment for HIV increases the risk of obesity and insulin resistance. Five-year mortality proportions of patients with diabetes varied from 4-57%. Screening studies identified high proportions (> 40%) with previously undiagnosed diabetes, and low levels of adequate glucose control among previously diagnosed diabetics. Barriers to accessing diagnosis and treatment included a lack of diagnostic tools and glucose monitoring equipment and high cost of diabetes treatment. The total annual cost of diabetes in the region was estimated at US$67.03 billion, or US$8836 per diabetic patient. Conclusion Diabetes exerts a significant burden in the region, and this is expected to increase. Many diabetic patients face significant challenges accessing diagnosis and treatment, which contributes to the high mortality and prevalence of complications observed. The significant interactions between diabetes and important infectious diseases highlight the need and opportunity for health planners to develop integrated responses to communicable and non-communicable diseases.
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              Cost-of-illness analysis. What room in health economics?

              Cost-of-illness (COI) was the first economic evaluation technique used in the health field. The principal aim was to measure the economic burden of illness to society. Its usefulness as a decision-making tool has however been questioned since its inception. The main criticism came from welfare economists who rejected COIs because they were not grounded in welfare economics theory. Other attacks related to the use of the human capital approach (HCA) to evaluate morbidity and mortality costs since it was said that the HCA had nothing to do with the value people attach to their lives. Finally, objections were made that COI could not be of any help to decision makers and that other forms of economic evaluation (e.g. cost-effectiveness, cost-benefit analysis) would be much more useful to those taking decisions and ranking priorities. Conversely, it is here suggested that COI can be a good economic tool to inform decision makers if it is considered from another perspective. COI is a descriptive study that can provide information to support the political process as well as the management functions at different levels of the healthcare organisations. To do that, the design of the study must be innovative, capable of measuring the true cost to society; to estimate the main cost components and their incidence over total costs; to envisage the different subjects who bear the costs; to identify the actual clinical management of illness; and to explain cost variability. In order to reach these goals, COI need to be designed as observational bottom-up studies.
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                Author and article information

                Contributors
                CMutyambizi@hsrc.ac.za
                m.pavlova@maastrichtuniversity.nl
                lumbwechola@hotmail.com
                chongoro@hsrc.ac.za
                w.groot@maastrichtuniversity.nl
                Journal
                Global Health
                Global Health
                Globalization and Health
                BioMed Central (London )
                1744-8603
                16 January 2018
                16 January 2018
                2018
                : 14
                Affiliations
                [1 ]ISNI 0000 0001 0071 1142, GRID grid.417715.1, Population Health, Health Systems and Innovation, , Human Sciences Research Council, ; HSRC Building, 134 Pretorius Street, Pretoria, 0002 South Africa
                [2 ]Department of Health Services Research; CAPHRI, Maastricht University Medical Centre, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
                [3 ]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, School of Public Health, Faculty of Health Sciences, , University of the Witwatersrand, ; Johannesburg, South Africa
                Article
                318
                10.1186/s12992-017-0318-5
                5771003
                29338746
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: Foundation Study Fund for South African Students
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                © The Author(s) 2018

                Health & Social care

                healthcare costs, diabetes, africa, cost of illness, economic burden

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