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Global estimates of diabetes prevalence for 2013 and projections for 2035

      Abstract

      Introduction

      Diabetes is a serious and increasing global health burden and estimates of prevalence are essential for appropriate allocation of resources and monitoring of trends.

      Methods

      We conducted a literature search of studies reporting the age-specific prevalence for diabetes and used the Analytic Hierarchy Process to systematically select studies to generate estimates for 219 countries and territories. Estimates for countries without available source data were modelled from pooled estimates of countries that were similar in regard to geography, ethnicity, and economic development. Logistic regression was applied to generate smoothed age-specific prevalence estimates for adults 20–79 years which were then applied to population estimates for 2013 and 2035.

      Results

      A total of 744 data sources were considered and 174 included, representing 130 countries. In 2013, 382 million people had diabetes; this number is expected to rise to 592 million by 2035. Most people with diabetes live in low- and middle-income countries and these will experience the greatest increase in cases of diabetes over the next 22 years.

      Conclusion

      The new estimates of diabetes in adults confirm the large burden of diabetes, especially in developing countries. Estimates will be updated annually including the most recent, high-quality data available.

      Keywords

      1. Introduction

      Diabetes is one of the most common metabolic disorders in the world and the prevalence of diabetes in adults has been increasing in the last decades [
      • Shaw J.E.
      • Sicree R.A.
      • Zimmet P.Z.
      Global estimates of the prevalence of diabetes for 2010 and 2030.
      ,
      • Whiting D.R.
      • Guariguata L.
      • Weil C.
      • Shaw J.
      IDF Diabetes Atlas: global estimates of the prevalence of diabetes for 2011 and 2030.
      ]. Urbanisation has driven dramatic changes in lifestyle and in particular in developing countries. With these rapid transitions come accompanying increases in risk factors for noncommunicable diseases like type 2 diabetes. Estimates of the current and future burden of diabetes are important to appropriately allocate resources, drive health-promoting policies, and encourage action to prevent diabetes in future generations.
      The International Diabetes Federation (IDF) has produced estimates of diabetes prevalence since the year 2000 [
      Diabetes Atlas.
      ,
      Diabetes Atlas.
      ,
      Diabetes Atlas.
      ,
      IDF Diabetes Atlas.
      ,
      IDF Diabetes Atlas.
      ]. Previous estimates of the prevalence of diabetes have demonstrated a large and increasing burden, with significant regional variability. The estimates in this paper provide the latest figures based on the most recent and highest quality data on diabetes prevalence for 219 countries and territories.

      2. Methods

      The methodology applied to generate the estimates is based largely on that used for previous estimates and is described in detail in Guariguata et al. [
      • Guariguata L.
      • Whiting D.
      • Weil C.
      • Unwin N.
      The International Diabetes Federation Diabetes Atlas methodology for estimating global and national prevalence of diabetes in adults.
      ]. Briefly, a literature search of PubMed, Medline, and Google Scholar for data sources reporting the age-specific prevalence of diabetes conducted from January 1980 through April 2013 using the search terms: ‘diabetes’ or ‘impaired glucose tolerance’ and ‘prevalence’ and ‘country name’ or ‘region/continent’; ‘cardiovascular risk factors’ and ‘country name or region/continent’. In addition, data sources were gathered from national health surveys conducted by governments, or non-governmental organisations such as the World Health Organization or World Health Surveys. Relevant citations from published literature were also reviewed and investigators within the IDF network were consulted to identify data sources.
      Studies were considered for inclusion that reported age-specific prevalence of diabetes for at least three age-groups for adults between 20 and 79 years. Methodological information from studies was abstracted and classified by the following: method of diagnosis; sample size; study type (e.g. population-based, clinic-based, diabetes registry, medical records review); representation (e.g. nationally representative, regionally representative, single city or village, single ethnic group or cohort); age of the data source; type of publication (e.g. peer-reviewed publication, national report).
      Using the classification criteria described above, a scoring system was developed using the Analytic Hierarchy Process [
      • Saaty T.L.
      Decision making with the analytic hierarchy process.
      ] which allows the comparison of different parameters (e.g. study type versus type of publication) to create a system of weights whereby each criterion for characterisation receives a corresponding score. Experts from the IDF network were asked to complete pairwise comparisons of criteria and a composite score based on the collective opinion was derived. Additional experts were consulted in 2013, producing an updated composite score. The updated scores are available in the online appendix.
      The scores for the criteria characterising each element in each study were summed to obtain an overall study score which was used in the selection process. Scores were plotted and produced a bimodal distribution with a smaller cluster at high scores (those scoring 0.5 and above), and a second large cluster ranging from 0.2 to 0.5. The median score was 0.32. Thresholds were selected based on the overall distribution of the scores with one top threshold in the nadir of the first cluster and a bottom threshold at the median. Studies that scored above an upper threshold (0.5) were always selected and those that scored below a lower threshold (0.32) were excluded. Studies scoring between 0.32 and 0.5 were considered for selection if no studies scoring above 0.5 were available from the same country. If considered, the top-scoring study in this middle range and any study scoring within 0.06 of the top-scoring study were selected. In countries where more than one study was selected, the age-specific prevalence of diabetes was calculated using a weighted average taking into account the underlying study scores for that country. Studies which scored most highly were nationally representative, conducted in the last 5 years, based on OGTT, and published in peer-reviewed literature.
      When no studies were available for a country, studies from countries matched for geographic region, income group, ethnicity, and IDF Region were aggregated. The groupings used for these extrapolated estimates are available in the online appendix.
      Studies were excluded that did not contain sufficient methodological information for characterisation, did not provide enough data on age-specific prevalence of diabetes, were conducted in hospital or clinic-based settings, were based only on treated diabetes, or were conducted before 1980. In addition, duplicates were removed where multiple publications were referencing the same study population or where an update of a survey was conducted using the same sampling frame (e.g. repeated national health surveys), previous ones were excluded. Studies reporting only on type 1 diabetes, or newly diagnosed diabetes were excluded.

      2.1 Statistical methods

      Statistical programming was done using the R statistical program version 2.15.2 [
      • R Core Team
      R: a language and environment for statistical computing.
      ]. The age- and sex-specific prevalence of diabetes was calculated for urban and rural settings for each country using logistic regression with diabetes prevalence as the dependent variable and age and a quadratic term for age as the independent variables. Where data were not available stratified by urban and rural setting, a ratio was applied to estimate the proportion of diabetes for each setting derived from aggregated data available within a data region together with the percentage urbanisation by country available from the UN Population Division to estimate the proportion of diabetes in urban and rural settings. Where sex-specific data were not available in the study, the distribution of diabetes in males and females was assumed to be the same. If a study was based only on self-reported diabetes, an estimate of undiagnosed diabetes was derived from proportions reported in population-based studies in the same data region. Full details of the methods and results on estimates of undiagnosed diabetes are available from Beagley et al. [
      • Beagley J.
      • Guariguata L.
      • Weil C.
      • Motala A.A.
      Global estimates of undiagnosed diabetes in adults.
      ].
      The calculated age-, sex- and setting-specific estimates were then multiplied by corresponding estimates of population for 2013 and 2035 for each of 219 countries and territories to produce cases of diabetes in adults. Prevalence estimates were standardised using the WHO Standard Population [
      • Ahmad O.B.
      • Boschi-Pinto C.
      • Lopez A.D.
      • Murray C.J.
      • Lozano R.
      • Inoue M.
      Age standardization of rates: a new WHO standard.
      ].
      The number of people with diabetes for each of the seven IDF Regions (Africa (AFR); Europe (EUR); Middle East and North Africa (MENA); North America and Caribbean (NAC); South and Central America (SACA); South-East Asia (SEA); and the Western Pacific (WP)) and World Bank income group (low-income (LIC); lower middle-income (LMIC); upper middle-income (UMIC); and high-income (HIC)) were calculated by aggregating the numbers of people with diabetes for each country within the respective regions. Global estimates were calculated by aggregating the total cases of diabetes.

      3. Results

      From the literature search, 744 data sources were identified representing 162 countries. Of these, 174 were selected representing 130 countries. These data produced an estimate of 381.8 million adults in 219 countries and territories with diabetes for 2013; and projected the number to rise to 591.9 million in 2035. The estimates derived from these sources for the 80 most populous countries (with adult populations greater than 6.5 million) are presented in Table 1 and the underlying data sources are presented in Table 2. Sixteen country estimates presented in the table were based on extrapolation. Detailed estimates of prevalence and numbers of people with diabetes on all 219 countries and territories are presented in the online appendix.
      Table 1Prevalence of diabetes and estimated number of people with diabetes (20–79 years) for 2013 and 2035: 80 most populous countries.
      Country/territoryPrevalence adjusted to the national population (%)Prevalence adjusted to the world population
      Comparative prevalence.
      (%)
      Diabetes cases (20–79) in 1000sMean annual increment (000s)Proportional change in adult population from 2013 to 2035 (%)Proportional change in number of people with diabetes from 2013 to 2035 (%)
      201320352013203520132035
      AFR
       Angola2.22.42.93.119945812112.6130.5
       Burkina Faso3.23.43.83.823850512104.7112.3
       Cameroon4.95.65.96.449810822789.7117.3
       Cote d’Ivoire5.25.76.06.45029652174.292.5
       Democratic Republic of the Congo5.46.26.16.9159436019195.2125.9
       Ethiopia4.45.14.95.518524418117103.5138.5
       Ghana3.43.73.83.94408191770.286.1
       Kenya3.64.44.64.974917464591.1133.0
       Madagascar3.33.53.83.835273918101.1109.8
       Malawi5.35.65.55.837280220103.7115.3
       Mozambique2.52.82.83.22785881488.0111.3
       Niger4.34.74.24.430678222136.9155.3
       Nigeria5.05.55.86.33922816019389.8108.1
       South Africa8.39.99.39.9264638605522.445.9
       Tanzania (United Republic of)7.88.69.09.71707381596102.9123.5
       Uganda4.14.94.85.6625166847126.5166.9
       Zimbabwe8.89.99.710.460112563086.0109.1
      EUR
       Belarus6.37.45.15.14454601−13.13.4
       Belgium6.47.34.84.851560443.617.2
       Czech Republic9.210.86.97.07568725−1.415.4
       France7.58.25.45.533753961277.117.4
       Germany11.914.18.38.37560810925−9.37.3
       Greece7.08.64.84.95856955−3.418.8
       Hungary7.68.56.06.15735911−8.13.1
       Italy7.99.85.15.23626435433−2.920.1
       Kazakhstan4.95.85.05.05267541019.943.4
       Netherlands7.59.05.25.3914110180.220.4
       Poland6.57.95.25.21880213312−6.813.5
       Portugal13.015.89.69.8103212339−2.019.5
       Romania5.16.44.04.08519605−9.912.8
       Russian Federation10.011.68.38.310,92411,19512−11.32.5
       Serbia12.414.79.910.28729232−11.25.8
       Spain10.814.48.28.337915179632.836.6
       Sweden6.46.64.74.743949838.713.5
       Turkey14.618.514.915.1704311,78621632.367.3
       Ukraine3.03.42.52.51044969−3−17.6−7.2
       United Kingdom6.67.44.95.029753619298.521.7
       Uzbekistan5.07.16.46.588117343939.196.9
      MENA
       Afghanistan6.36.68.38.5795184248120.0131.8
       Algeria6.68.47.57.8164028895738.876.2
       Egypt15.618.616.817.7751113,07325346.074.1
       Iran (Islamic Republic of)8.412.39.910.14396839618230.591.0
       Iraq7.48.89.59.7122628047294.5128.7
       Morocco7.39.27.88.2149125084633.968.2
       Pakistan6.88.17.98.1671312,79827759.490.7
       Saudi Arabia20.227.123.924.53651749917553.4105.4
       Sudan7.78.79.69.8140229046885.1107.1
       Syrian Arab Republic7.49.28.99.186919024775.0118.9
       Tunisia9.212.29.49.868611302024.564.8
       United Arab Emirates10.023.119.019.474625758349.8245.3
       Yemen6.17.58.58.770816334288.7130.6
      NAC
       Canada10.211.77.97.9263834633714.331.3
       Mexico11.815.212.612.6872315,68431639.479.8
       United States of America10.911.69.29.224,40229,71824214.821.8
      SACA
       Argentina6.06.75.75.7160822232823.338.2
       Brazil9.011.79.29.211,93419,22333124.461.1
       Chile10.412.79.59.5125418412720.146.8
       Colombia7.18.27.37.3213533405536.256.4
       Cuba9.712.78.18.181410229−3.725.5
       Ecuador5.76.25.95.95308501546.860.4
       Guatemala9.09.810.910.966113763290.6108.1
       Peru4.34.94.54.578612802240.962.8
       Venezuela (Bolivarian Rep. of)6.67.87.07.0123220683841.567.9
      SEA
       Bangladesh5.58.26.37.5508910,91626544.7114.5
       India8.610.59.19.765,076109,028199837.067.5
       Nepal4.55.44.95.367412532654.285.8
       Sri  Lanka8.09.57.68.2112815531916.937.7
      WP
       Australia10.011.37.87.8164923123024.140.2
       Cambodia2.53.43.03.22214451048.7101.1
       China9.613.09.09.598,407142,66320127.345.0
       Democratic People's Republic of Korea7.38.86.77.0125217322213.638.4
       Indonesia5.66.75.85.9855414,15225437.865.4
       Japan7.68.25.15.272046722−22−14.2−6.7
       Malaysia10.112.210.910.9191332996342.872.4
       Myanmar5.78.06.16.9198934386623.672.9
       Philippines6.07.16.97.23256601412556.384.7
       Republic of Korea8.911.47.57.533244511545.635.7
       Taiwan9.813.18.38.31721229926−0.333.6
       Thailand6.48.35.75.731514287524.836.1
       Viet Nam5.48.25.86.73299633813825.292.1
      a Adjusted to the WHO Standard 2001
      • Ahmad O.B.
      • Boschi-Pinto C.
      • Lopez A.D.
      • Murray C.J.
      • Lozano R.
      • Inoue M.
      Age standardization of rates: a new WHO standard.
      .
      Table 2Data sources for estimates of diabetes prevalence for the 80 most populous countries.
      IDF RegionCountryData source(s)
      Africa (AFR)
      AngolaEvaristo-Neto et al.
      • Evaristo-Neto A.D.
      • Foss-Freitas M.C.
      • Foss M.C.
      Prevalence of diabetes mellitus and impaired glucose tolerance in a rural community of Angola.
      Burkina FasoGambia
      • Van der Sande M.A.
      • Bailey R.
      • Faal H.
      • Banya W.A.
      • Dolin P.
      • Nyan O.A.
      • et al.
      Nationwide prevalence study of hypertension and related non-communicable diseases in The Gambia.
      , Malawi
      • Ministry of Health
      Malawi STEPS Noncommunicable Disease Risk Factors Survey 2009.
      , Benin
      • Djrolo F.
      • Houinato D.
      • Gbary A.
      • Akoha R.
      • Djigbénoudé O.
      • Sègnon J.
      Prevalence of diabetes mellitus in the adult population at Cotonou, Benin.
      ,
      • Ministry of Health Benin
      Benin STEPS Noncommunicable Disease Risk Factors Survey 2008.
      , Mozambique
      • Silva-Matos C.
      • Gomes A.
      • Azevedo A.
      • Damasceno A.
      • Prista A.
      • Lunet N.
      Diabetes in Mozambique: prevalence, management and healthcare challenges.
      , Togo
      Togo Ministry of Health
      , Zimbabwe
      • Ministry of Health & Child Welfare, University of Zimbabwe
      Zimbabwe – STEPS Noncommunicable Disease Risk Factors Survey 2005.
      , Guinea
      • Baldé N.-M.
      • Diallo I.
      • Baldé M.-D.
      • Barry I.-S.
      • Kaba L.
      • Diallo M.-M.
      • et al.
      Diabetes and impaired fasting glucose in rural and urban populations in Futa Jallon (Guinea): prevalence and associated risk factors.
      CameroonCamBoD Project
      • Health of Population in Transition Research Group – Cameroon
      Cameroon Burden of Diabetes (CamBoD) Project: Second Survey Report, 2007.
      Côte d’IvoireCameroon
      • Health of Population in Transition Research Group – Cameroon
      Cameroon Burden of Diabetes (CamBoD) Project: Second Survey Report, 2007.
      Democratic Republic of the CongoKenya
      • Christensen D.L.
      • Friis H.
      • Mwaniki D.L.
      • Kilonzo B.
      • Tetens I.
      • Boit M.K.
      • et al.
      Prevalence of glucose intolerance and associated risk factors in rural and urban populations of different ethnic groups in Kenya.
      , Niger
      • Republique du Niger Ministere de la Sante Publique
      Niger – STEPS Noncommunicable Disease Risk Factors Survey 2007.
      , Mauritania
      • Meiloud G.
      • Arfa I.
      • Kefi R.
      • Abdelhamid I.
      • Veten F.
      • Lasram K.
      • et al.
      Type 2 diabetes in Mauritania: prevalence of the undiagnosed diabetes, influence of family history and maternal effect.
      , Tanzania
      • Ministry of Health Tanzania
      Tanzania STEPS Noncommunicable Disease Risk Factors Survey 2012.
      , Comoros
      • Solet J.-L.
      • Baroux N.
      • Pochet M.
      • Benoit-Cattin T.
      • De Montera A.-M.
      • Sissoko D.
      • et al.
      Prevalence of type 2 diabetes and other cardiovascular risk factors in Mayotte in 2008: the MAYDIA study.
      , Mali
      • Fisch A.
      • Pichard E.
      • Prazuck T.
      • Leblanc H.
      • Sidibe Y.
      • Brücker G.
      Prevalence and risk factors of diabetes mellitus in the rural region of Mali (West Africa): a practical approach.
      EthiopiaKenya
      • Christensen D.L.
      • Friis H.
      • Mwaniki D.L.
      • Kilonzo B.
      • Tetens I.
      • Boit M.K.
      • et al.
      Prevalence of glucose intolerance and associated risk factors in rural and urban populations of different ethnic groups in Kenya.
      , Niger
      • Republique du Niger Ministere de la Sante Publique
      Niger – STEPS Noncommunicable Disease Risk Factors Survey 2007.
      , Mauritania
      • Meiloud G.
      • Arfa I.
      • Kefi R.
      • Abdelhamid I.
      • Veten F.
      • Lasram K.
      • et al.
      Type 2 diabetes in Mauritania: prevalence of the undiagnosed diabetes, influence of family history and maternal effect.
      , Tanzania
      • Ministry of Health Tanzania
      Tanzania STEPS Noncommunicable Disease Risk Factors Survey 2012.
      , Comoros
      • Solet J.-L.
      • Baroux N.
      • Pochet M.
      • Benoit-Cattin T.
      • De Montera A.-M.
      • Sissoko D.
      • et al.
      Prevalence of type 2 diabetes and other cardiovascular risk factors in Mayotte in 2008: the MAYDIA study.
      , Mali
      • Fisch A.
      • Pichard E.
      • Prazuck T.
      • Leblanc H.
      • Sidibe Y.
      • Brücker G.
      Prevalence and risk factors of diabetes mellitus in the rural region of Mali (West Africa): a practical approach.
      GhanaGambia
      • Van der Sande M.A.
      • Bailey R.
      • Faal H.
      • Banya W.A.
      • Dolin P.
      • Nyan O.A.
      • et al.
      Nationwide prevalence study of hypertension and related non-communicable diseases in The Gambia.
      , Malawi
      • Ministry of Health
      Malawi STEPS Noncommunicable Disease Risk Factors Survey 2009.
      , Benin
      • Djrolo F.
      • Houinato D.
      • Gbary A.
      • Akoha R.
      • Djigbénoudé O.
      • Sègnon J.
      Prevalence of diabetes mellitus in the adult population at Cotonou, Benin.
      ,
      • Ministry of Health Benin
      Benin STEPS Noncommunicable Disease Risk Factors Survey 2008.
      , Mozambique
      • Silva-Matos C.
      • Gomes A.
      • Azevedo A.
      • Damasceno A.
      • Prista A.
      • Lunet N.
      Diabetes in Mozambique: prevalence, management and healthcare challenges.
      , Togo
      Togo Ministry of Health
      , Zimbabwe
      • Ministry of Health & Child Welfare, University of Zimbabwe
      Zimbabwe – STEPS Noncommunicable Disease Risk Factors Survey 2005.
      , Guinea
      • Baldé N.-M.
      • Diallo I.
      • Baldé M.-D.
      • Barry I.-S.
      • Kaba L.
      • Diallo M.-M.
      • et al.
      Diabetes and impaired fasting glucose in rural and urban populations in Futa Jallon (Guinea): prevalence and associated risk factors.
      KenyaChristensen et al.
      • Christensen D.L.
      • Friis H.
      • Mwaniki D.L.
      • Kilonzo B.
      • Tetens I.
      • Boit M.K.
      • et al.
      Prevalence of glucose intolerance and associated risk factors in rural and urban populations of different ethnic groups in Kenya.
      MadagascarGambia
      • Van der Sande M.A.
      • Bailey R.
      • Faal H.
      • Banya W.A.
      • Dolin P.
      • Nyan O.A.
      • et al.
      Nationwide prevalence study of hypertension and related non-communicable diseases in The Gambia.
      , Malawi
      • Ministry of Health
      Malawi STEPS Noncommunicable Disease Risk Factors Survey 2009.
      , Benin
      • Djrolo F.
      • Houinato D.
      • Gbary A.
      • Akoha R.
      • Djigbénoudé O.
      • Sègnon J.
      Prevalence of diabetes mellitus in the adult population at Cotonou, Benin.
      ,
      • Ministry of Health Benin
      Benin STEPS Noncommunicable Disease Risk Factors Survey 2008.
      , Mozambique
      • Silva-Matos C.
      • Gomes A.
      • Azevedo A.
      • Damasceno A.
      • Prista A.
      • Lunet N.
      Diabetes in Mozambique: prevalence, management and healthcare challenges.
      , Togo
      Togo Ministry of Health
      , Zimbabwe
      • Ministry of Health & Child Welfare, University of Zimbabwe
      Zimbabwe – STEPS Noncommunicable Disease Risk Factors Survey 2005.
      , Guinea
      • Baldé N.-M.
      • Diallo I.
      • Baldé M.-D.
      • Barry I.-S.
      • Kaba L.
      • Diallo M.-M.
      • et al.
      Diabetes and impaired fasting glucose in rural and urban populations in Futa Jallon (Guinea): prevalence and associated risk factors.
      MozambiqueSilva-Matos et al.
      • Silva-Matos C.
      • Gomes A.
      • Azevedo A.
      • Damasceno A.
      • Prista A.
      • Lunet N.
      Diabetes in Mozambique: prevalence, management and healthcare challenges.
      NigerNiger STEPs survey
      • Republique du Niger Ministere de la Sante Publique
      Niger – STEPS Noncommunicable Disease Risk Factors Survey 2007.
      NigeriaCameroon
      • Health of Population in Transition Research Group – Cameroon
      Cameroon Burden of Diabetes (CamBoD) Project: Second Survey Report, 2007.
      South AfricaMotala et al.
      • Motala A.A.
      • Esterhuizen T.
      • Gouws E.
      • Pirie F.J.
      • Omar M.A.K.
      Diabetes and other disorders of glycemia in a rural South African community: prevalence and associated risk factors.
      , Peer et al.
      • Peer N.
      • Steyn K.
      • Lombard C.
      • Lambert E.V.
      • Vythilingum B.
      • Levitt N.S.
      Rising diabetes prevalence among urban-dwelling black South Africans.
      UgandaKenya
      • Christensen D.L.
      • Friis H.
      • Mwaniki D.L.
      • Kilonzo B.
      • Tetens I.
      • Boit M.K.
      • et al.
      Prevalence of glucose intolerance and associated risk factors in rural and urban populations of different ethnic groups in Kenya.
      , Niger
      • Republique du Niger Ministere de la Sante Publique
      Niger – STEPS Noncommunicable Disease Risk Factors Survey 2007.
      , Mauritania
      • Meiloud G.
      • Arfa I.
      • Kefi R.
      • Abdelhamid I.
      • Veten F.
      • Lasram K.
      • et al.
      Type 2 diabetes in Mauritania: prevalence of the undiagnosed diabetes, influence of family history and maternal effect.
      , Tanzania
      • Ministry of Health Tanzania
      Tanzania STEPS Noncommunicable Disease Risk Factors Survey 2012.
      , Comoros
      • Solet J.-L.
      • Baroux N.
      • Pochet M.
      • Benoit-Cattin T.
      • De Montera A.-M.
      • Sissoko D.
      • et al.
      Prevalence of type 2 diabetes and other cardiovascular risk factors in Mayotte in 2008: the MAYDIA study.
      , Mali
      • Fisch A.
      • Pichard E.
      • Prazuck T.
      • Leblanc H.
      • Sidibe Y.
      • Brücker G.
      Prevalence and risk factors of diabetes mellitus in the rural region of Mali (West Africa): a practical approach.
      Tanzania (United Republic of)Tanzania STEPs survey
      • Ministry of Health Tanzania
      Tanzania STEPS Noncommunicable Disease Risk Factors Survey 2012.
      ZimbabweZimbabwe STEPs survey
      • Ministry of Health & Child Welfare, University of Zimbabwe
      Zimbabwe – STEPS Noncommunicable Disease Risk Factors Survey 2005.
      Europe (EUR)
      BelarusLithuania
      • European Health Interview Survey
      European Health Interview Survey Lithuania.
      , Poland
      • Polakowska M.
      • Piotrowski W.
      Incidence of diabetes in the Polish population: results of the Multicenter Polish Population Health Status Study – WOBASZ.
      , Russian Federation,
      • Dogadin S.A.
      • Mashtakov B.P.
      • Taranushenko T.E.
      Prevalence of type 2 diabetes in northern populations of Siberia.
      , Latvia
      • Central Statistical Bureau
      European Health Interview Survey Latvia.
      Belgiumvan der Heyden et al.
      • Demarest S.
      • Drieskens S.
      • Gisle L.
      • Van der Heyden J.
      • Tafforeau J.
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      Czech RepublicCzech Republic Health Survey
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      European Health Interview Survey Czech Republic.
      FranceBonaldi et al.
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      A first national prevalence estimate of diagnosed and undiagnosed diabetes in France in 18- to 74-year-old individuals: the French Nutrition and Health Survey 2006/2007.
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      Prevalence of type 2 diabetes and impaired fasting glucose in the middle-aged population of three French regions – the MONICA study 1995–97.
      GermanyHeidemann et al.
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      Prevalence of known diabetes in German adults aged 25–69 years: results from national health surveys over 15 years.
      GreeceTentolouris et al.
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      Prevalence of diabetes mellitus and obesity in the general adult population of Greece: a door-to-door epidemiological study.
      HungaryJermendy et al.
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      Prevalence rate of diabetes mellitus and impaired fasting glycemia in Hungary: cross-sectional study on nationally representative sample of people aged 20–69 years.
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      Prevalence of diabetes in a large, nationally representative population sample in Hungary.
      ItalyCricelli et al.
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      Prevalence estimates for chronic diseases in Italy: exploring the differences between self-report and primary care databases.
      , Italian health survey
      • Instituto nazionale di statistica
      Condizioni di salute, fattori di rischio ricorso ai servizi sanitari Anno 2005.
      NetherlandsNetherlands Health Interview Survey
      • National Institute for Public Health and the Environment
      POLS Health Interview Survey.
      PolandPolakowska and Piotrowski
      • Dogadin S.A.
      • Mashtakov B.P.
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      Prevalence of type 2 diabetes in northern populations of Siberia.
      PortugalGardete-Correia et al.
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      First diabetes prevalence study in Portugal: PREVADIAB study.
      RomaniaRomanian Health Interview Survey
      • National Institute of Statistics Romania
      European Health Interview Survey Romania.
      Russian FederationDogadin et al.
      • Dogadin S.A.
      • Mashtakov B.P.
      • Taranushenko T.E.
      Prevalence of type 2 diabetes in northern populations of Siberia.
      SerbiaRomania
      • National Institute of Statistics Romania
      European Health Interview Survey Romania.
      , Bulgaria
      • Borissova A.M.
      • Shinkov A.
      • Kovatcheva R.
      Prevalence of diabetes in Bulgaria and the significance of the risk factors: age, obesity and family history.
      ,
      • Bulgarian National Statistical Institute
      European Health Interview Survey Bulgaria.
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      Twelve-year trends in the prevalence and risk factors of diabetes and prediabetes in Turkish adults.
      SpainSoriguer et al.
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      Prevalence of diabetes mellitus and impaired glucose regulation in Spain: the Diabetes study.
      SwedenSweden Living Conditions Survey
      • Statistiska Centralbyrån
      Living Conditions Surveys (ULF/SILC) – Statistics Sweden 2004.
      TurkeySatman et al.
      • Satman I.
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      Twelve-year trends in the prevalence and risk factors of diabetes and prediabetes in Turkish adults.
      UkraineAlbania
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      Prevalence of type 2 diabetes in the southwest Albanian adult population.
      United KingdomImkampe and Gulliford
      • Imkampe A.K.
      • Gulliford M.C.
      Increasing socio-economic inequality in type 2 diabetes prevalence – repeated cross-sectional surveys in England 1994–2006.
      , Health Survey for England
      • Health and Social Care Information Centre
      Health Survey for England – 2004.
      , Pierce et al.
      • Pierce M.B.
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      • Steel N.
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      Undiagnosed diabetes – data from the English longitudinal study of ageing.
      UzbekistanKing et al.
      • King H.
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      • Ashworth L.
      • Dobo M.G.
      Glucose intolerance and associated factors in the Fergana Valley, Uzbekistan.
      Middle East and North Africa (MENA)
      AfghanistanPalestine
      • Abdul-Rahim H.F.
      • Husseini A.
      • Giacaman R.
      • Jervell J.
      • Bjertness E.
      Diabetes mellitus in an urban Palestinian population: prevalence and associated factors.
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      • Husseini A.
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      • Jervell J.
      • Bjertness E.
      Prevalence of diabetes mellitus and impaired glucose tolerance in a rural Palestinian population.
      , Iraq
      • Ministry of Health
      Republic of Iraq, Iraq Family Health Survey Report IFHS 2006/7.
      ,
      • Ministry of Health, Directorate of Public Health and Primary Health Care, Ministry of Planning and Development Cooperation, Central Organization for Statistic and Information
      Iraq STEPS Noncommunicable Disease Risk Factors Survey 2006.
      , Jordan
      • Ajlouni K.
      • Jaddou H.
      • Batieha A.
      Diabetes and impaired glucose tolerance in Jordan: prevalence and associated risk factors.
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      • Hadaddin R.
      • Brown D.W.
      • Walke H.
      Prevalence of selected chronic, noncommunicable disease risk factors in Jordan: results of the 2007 Jordan Behavioral Risk Factor Surveillance Survey.
      ,
      • Ministry of Health
      Jordan STEPS Noncommunicable Disease Risk Factors Survey 2004.
      ,
      • Zindah M.
      • Belbeisi A.
      • Walke H.
      • Mokdad A.H.
      Obesity and diabetes in Jordan: findings from the behavioral risk factor surveillance system, 2004.
      , Pakistan
      • Shera A.S.
      • Jawad F.
      • Maqsood A.
      Prevalence of diabetes in Pakistan.
      AlgeriaMalek et al.
      • Malek R.
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      • Bendib W.
      • et al.
      Prevalence of type 2 diabetes mellitus and glucose intolerance in the Setif area (Algeria).
      , Algeria STEPs Survey
      • Ministry of Health Algeria, World Health Organization
      Algeria STEPS Noncommunicable Disease Risk Factors Survey 2003.
      EgyptEgypt STEPs survey
      • Ministry of Health
      Egypt STEPS Noncommunicable Disease Risk Factors Survey 2011–2012.
      IraqIraq Family Health Survey 2006/7
      • Ministry of Health
      Republic of Iraq, Iraq Family Health Survey Report IFHS 2006/7.
      , Iraq STEPs survey
      • Ministry of Health, Directorate of Public Health and Primary Health Care, Ministry of Planning and Development Cooperation, Central Organization for Statistic and Information
      Iraq STEPS Noncommunicable Disease Risk Factors Survey 2006.
      Islamic Republic of IranEsteghamati et al.
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      • et al.
      Third national Surveillance of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007) in Iran: methods and results on prevalence of diabetes, hypertension, obesity, central obesity, and dyslipidemia.
      , Iran STEPs survey
      • Ministry of Health
      Islamic Republic of Iran STEPS Noncommunicable Disease Risk Factors Survey 2007.
      MoroccoTazi et al.
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      Prevalence of the main cardiovascular risk factors in Morocco: results of a National Survey, 2000.
      PakistanShera et al.
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      Prevalence of diabetes in Pakistan.
      Saudi ArabiaAl-Daghri et al.
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      • et al.
      Diabetes mellitus type 2 and other chronic non-communicable diseases in the central region, Saudi Arabia (Riyadh cohort 2): a decade of an epidemic.
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      Diabetes mellitus in Saudi Arabia.
      , Warsy and El-Hazmi
      • Warsy A.S.
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      Diabetes mellitus, hypertension and obesity – common multifactorial disorders in Saudis.
      , Al-Nuaim
      • Al-Nuaim A.R.
      Prevalence of glucose intolerance in urban and rural communities in Saudi Arabia.
      , Saudi Arabia STEPs Survey
      • Ministry of Health
      Saudi Arabia – STEPS Noncommunicable Disease Risk Factors Survey 2005.
      SudanTunisia
      • Bouguerra R.
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      The global diabetes pandemic: the Tunisian experience.
      , Morocco
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      • Lahmouz F.
      • Sraïri J.E.
      • et al.
      Prevalence of the main cardiovascular risk factors in Morocco: results of a National Survey, 2000.
      , Egypt
      • Ministry of Health
      Egypt STEPS Noncommunicable Disease Risk Factors Survey 2011–2012.
      Syrian Arab RepublicPalestine
      • Abdul-Rahim H.F.
      • Husseini A.
      • Giacaman R.
      • Jervell J.
      • Bjertness E.
      Diabetes mellitus in an urban Palestinian population: prevalence and associated factors.
      ,
      • Husseini A.
      • Abdul-Rahim H.
      • Awartani F.
      • Jervell J.
      • Bjertness E.
      Prevalence of diabetes mellitus and impaired glucose tolerance in a rural Palestinian population.
      , Iraq
      • Ministry of Health
      Republic of Iraq, Iraq Family Health Survey Report IFHS 2006/7.
      ,
      • Ministry of Health, Directorate of Public Health and Primary Health Care, Ministry of Planning and Development Cooperation, Central Organization for Statistic and Information
      Iraq STEPS Noncommunicable Disease Risk Factors Survey 2006.
      , Jordan
      • Ajlouni K.
      • Jaddou H.
      • Batieha A.
      Diabetes and impaired glucose tolerance in Jordan: prevalence and associated risk factors.
      ,
      • Al-Nsour M.
      • Zindah M.
      • Belbeisi A.
      • Hadaddin R.
      • Brown D.W.
      • Walke H.
      Prevalence of selected chronic, noncommunicable disease risk factors in Jordan: results of the 2007 Jordan Behavioral Risk Factor Surveillance Survey.
      ,
      • Ministry of Health
      Jordan STEPS Noncommunicable Disease Risk Factors Survey 2004.
      ,
      • Zindah M.
      • Belbeisi A.
      • Walke H.
      • Mokdad A.H.
      Obesity and diabetes in Jordan: findings from the behavioral risk factor surveillance system, 2004.
      , Pakistan
      • Shera A.S.
      • Jawad F.
      • Maqsood A.
      Prevalence of diabetes in Pakistan.
      TunisiaBouguerra et al.
      • Bouguerra R.
      • Alberti H.
      • Salem L.B.
      • Rayana C.B.
      • Atti J.E.
      • Gaigi S.
      • et al.
      The global diabetes pandemic: the Tunisian experience.
      United Arab EmiratesMalik et al.
      • Malik M.
      • Bakir A.
      • Saab B.A.
      • Roglic G.
      • King H.
      Glucose intolerance and associated factors in the multi-ethnic population of the United Arab Emirates: results of a national survey.
      YemenPalestine
      • Abdul-Rahim H.F.
      • Husseini A.
      • Giacaman R.
      • Jervell J.
      • Bjertness E.
      Diabetes mellitus in an urban Palestinian population: prevalence and associated factors.
      ,
      • Husseini A.
      • Abdul-Rahim H.
      • Awartani F.
      • Jervell J.
      • Bjertness E.
      Prevalence of diabetes mellitus and impaired glucose tolerance in a rural Palestinian population.
      , Iraq
      • Ministry of Health
      Republic of Iraq, Iraq Family Health Survey Report IFHS 2006/7.
      ,
      • Ministry of Health, Directorate of Public Health and Primary Health Care, Ministry of Planning and Development Cooperation, Central Organization for Statistic and Information
      Iraq STEPS Noncommunicable Disease Risk Factors Survey 2006.
      , Jordan
      • Ajlouni K.
      • Jaddou H.
      • Batieha A.
      Diabetes and impaired glucose tolerance in Jordan: prevalence and associated risk factors.
      ,
      • Al-Nsour M.
      • Zindah M.
      • Belbeisi A.
      • Hadaddin R.
      • Brown D.W.
      • Walke H.
      Prevalence of selected chronic, noncommunicable disease risk factors in Jordan: results of the 2007 Jordan Behavioral Risk Factor Surveillance Survey.
      ,
      • Ministry of Health
      Jordan STEPS Noncommunicable Disease Risk Factors Survey 2004.
      ,
      • Zindah M.
      • Belbeisi A.
      • Walke H.
      • Mokdad A.H.
      Obesity and diabetes in Jordan: findings from the behavioral risk factor surveillance system, 2004.
      , Pakistan
      • Shera A.S.
      • Jawad F.
      • Maqsood A.
      Prevalence of diabetes in Pakistan.
      North America and Caribbean (NAC)
      CanadaNational Diabetes Surveillance System
      • Public Health Agency of Canada Government of Canada
      Report from the National Diabetes Surveillance System: Diabetes in Canada, 2009: Table of Contents – National Diabetes Surveillance System – Public Health Agency of Canada.
      MexicoENSANUT 2012
      • Instituto Nacional de Salud Pública
      Encuesta Nacional de Salud y Nutrición 2012. Resultados nacionales Primera edición.
      United States of AmericaNHANES 2012
      NHANES – National Health and Nutrition Examination Survey Homepage.
      South and Central America (SACA)
      Argentinade Sereday et al.
      • De Sereday M.S.
      • Gonzalez C.
      • Giorgini D.
      • De Loredo L.
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      • et al.
      Prevalence of diabetes, obesity, hypertension and hyperlipidemia in the central area of Argentina.
      , Escobedo et al.
      • Escobedo J.
      • Buitrón L.V.
      • Velasco M.F.
      • Ramírez J.C.
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      • et al.
      High prevalence of diabetes and impaired fasting glucose in urban Latin America: the CARMELA study.
      BrazilIser et al.
      • Iser B.P.M.
      • Claro R.M.
      • de Moura E.C.
      • Malta D.C.
      • Morais Neto O.L.
      Risk and protection factors for chronic non-communicable diseases by telephone survey – VIGITEL-2009.
      ChileEncuesta Nacional de Salud 2009–2011

      Ministry of Health, Chile. Encuesta nacional de salud, 2009–2010.

      ColombiaColombia STEPs survey – Santander
      • Ministry of Health Colombia
      Colombia STEPS Noncommunicable Disease Risk Factors Survey 2010.
      CubaDominican Republic
      • Pichardo R.
      • Gonzales A.R.
      • Ramirez W.
      • Escano F.
      • Rodriguez C.
      • Jimenez R.O.
      Estudio de los factores de riesgo cardiovasculary sindrome metabolico en la republica dominicana – EFRICARD II.
      , Colombia
      • Ministry of Health Colombia
      Colombia STEPS Noncommunicable Disease Risk Factors Survey 2010.
      , Brazil
      • Iser B.P.M.
      • Claro R.M.
      • de Moura E.C.
      • Malta D.C.
      • Morais Neto O.L.
      Risk and protection factors for chronic non-communicable diseases by telephone survey – VIGITEL-2009.
      , Costa Rica
      • The Central American Diabetes Initiative
      The Central America Diabetes Initiative (CAMDI): Survey of Diabetes, Hypertension and Chronic Disease Risk Factors.
      ,
      • Araya M.R.
      • Hernández A.G.A.
      • Vargas G.P.
      • Trejos A.M.
      Prevalencia de diabetes mellitus auto-reportada en Costa Rica, 1998.
      , Venezuela
      • Escobedo J.
      • Buitrón L.V.
      • Velasco M.F.
      • Ramírez J.C.
      • Hernández R.
      • Macchia A.
      • et al.
      High prevalence of diabetes and impaired fasting glucose in urban Latin America: the CARMELA study.
      EcuadorEscobedo et al.
      • Escobedo J.
      • Buitrón L.V.
      • Velasco M.F.
      • Ramírez J.C.
      • Hernández R.
      • Macchia A.
      • et al.
      High prevalence of diabetes and impaired fasting glucose in urban Latin America: the CARMELA study.
      GuatemalaCAMDi Guatemala
      • The Central American Diabetes Initiative
      The Central America Diabetes Initiative (CAMDI): Survey of Diabetes, Hypertension and Chronic Disease Risk Factors.
      PeruEscobedo et al.
      • Escobedo J.
      • Buitrón L.V.
      • Velasco M.F.
      • Ramírez J.C.
      • Hernández R.
      • Macchia A.
      • et al.
      High prevalence of diabetes and impaired fasting glucose in urban Latin America: the CARMELA study.
      VenezuelaEscobedo et al.
      • Escobedo J.
      • Buitrón L.V.
      • Velasco M.F.
      • Ramírez J.C.
      • Hernández R.
      • Macchia A.
      • et al.
      High prevalence of diabetes and impaired fasting glucose in urban Latin America: the CARMELA study.
      South-East Asia (SEA)
      BangladeshBangladesh STEPs Survey
      • Bangladesh Ministry of Health
      Bangladesh STEPS Noncommunicable Disease Risk Factors Survey 2010.
      IndiaAnjana et al.
      • Anjana R.M.
      • Pradeepa R.
      • Deepa M.
      • Datta M.
      • Sudha V.
      • Unnikrishnan R.
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      Prevalence of diabetes and prediabetes (impaired fasting glucose and/or impaired glucose tolerance) in urban and rural India: phase I results of the Indian Council of Medical Research-INdia DIABetes (ICMR-INDIAB) study.
      NepalMehta et al.
      • Mehta K.D.
      • Karki P.
      • Lamsal M.
      • Paudel I.S.
      • Majhi S.
      • Das B.K.L.
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      Hyperglycemia, glucose intolerance, hypertension and socioeconomic position in eastern Nepal.
      , Ono et al.
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      • Yanagida J.-I.
      • Rai G.
      • et al.
      The prevalence of type 2 diabetes mellitus and impaired fasting glucose in semi-urban population of Nepal.
      , Singh and Bhattarai
      • Singh D.L.
      • Bhattarai M.D.
      High prevalence of diabetes and impaired fasting glycaemia in urban Nepal.
      Sri LankaKatulanda et al.
      • Katulanda P.
      • Constantine G.R.
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      • Sheriff R.
      • Seneviratne R.D.A.
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      Prevalence and projections of diabetes and pre-diabetes in adults in Sri Lanka – Sri Lanka Diabetes, Cardiovascular Study (SLDCS).
      , Wijewardene et al.
      • Wijewardene K.
      • Mohideen M.R.
      • Mendis S.
      • Fernando D.S.
      • Kulathilaka T.
      • Weerasekara D.
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      Prevalence of hypertension, diabetes and obesity: baseline findings of a population based survey in four provinces in Sri Lanka.
      Western Pacific (WP)
      AustraliaAustralia Health Survey 2011
      • Australian Bureau of Statistics
      Australian Health Survey 2011–2012 First Results.
      CambodiaCambodia STEPs Survey
      • Ministry of Health Cambodia
      Cambodia Marshall Islands STEPS Noncommunicable Disease Risk Factors Survey 2010.
      ChinaLi et al.
      • Li R.
      • Lu W.
      • Jiang Q.W.
      • Li Y.Y.
      • Zhao G.M.
      • Shi L.
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      Increasing prevalence of type 2 diabetes in Chinese adults in Shanghai.
      , Yang et al.
      • Yang W.
      • Lu J.
      • Weng J.
      • Jia W.
      • Ji L.
      • Xiao J.
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      Prevalence of diabetes among men and women in China.
      Democratic People's Republic of KoreaCambodia
      • Ministry of Health Cambodia
      Cambodia Marshall Islands STEPS Noncommunicable Disease Risk Factors Survey 2010.
      , Viet Nam
      • Nguyen Q.N.
      • Pham S.T.
      • Do L.D.
      • Nguyen V.L.
      • Wall S.
      • Weinehall L.
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      Cardiovascular disease risk factor patterns and their implications for intervention strategies in Vietnam.
      , Myanmar
      • Ko-Ko-Zaw
      • Tint-Swe-Latt
      • Phyu-Phyu-Aung
      • Thein-Gi-Thwin
      • Tin-Khine-Myint
      Prevalence of hypertension and its associated factors in the adult population in Yangon Division, Myanmar.
      IndonesiaMihardja et al.
      • Mihardja L.
      • Delima Manz H.S.
      • Ghani L.
      • Soegondo S.
      Prevalence and determinants of diabetes mellitus and impaired glucose tolerance in Indonesia (a part of basic health research/Riskesdas).
      JapanJapan National Health Survey
      • Ministry of Health
      National Health and Nutrition Survey Japan, 2007.
      MalaysiaLetchuman et al.
      • Letchuman G.R.
      • Wan Nazaimoon W.M.
      • Wan Mohamad W.B.
      • Chandran L.R.
      • Tee G.H.
      • Jamaiyah H.
      • et al.
      Prevalence of diabetes in the Malaysian National Health Morbidity Survey III 2006.
      , Malaysia STEPs survey
      • Ministry of Health
      Malaysia STEPS Noncommunicable Disease Risk Factors Survey 2002.
      , Rampal et al.
      • Rampal S.
      • Rampal L.
      • Rahmat R.
      • Zain A.M.
      • Yap Y.G.
      • Mohamed M.
      • et al.
      Variation in the prevalence, awareness, and control of diabetes in a multiethnic population: a nationwide population study in Malaysia.
      MyanmarKo-Ko-Zaw et al.
      • Ko-Ko-Zaw
      • Tint-Swe-Latt
      • Phyu-Phyu-Aung
      • Thein-Gi-Thwin
      • Tin-Khine-Myint
      Prevalence of hypertension and its associated factors in the adult population in Yangon Division, Myanmar.
      PhilippinesSy et al.
      • Sy R.G.
      • Morales D.D.
      • Dans A.L.
      • Paz-Pacheco E.
      • Punzalan F.E.R.
      • Abelardo N.S.
      • et al.
      Prevalence of atherosclerosis-related risk factors and diseases in the Philippines.
      Republic of KoreaChoi et al.
      • Choi Y.J.
      • Kim H.C.
      • Kim H.M.
      • Park S.W.
      • Kim J.
      • Kim D.J.
      Prevalence and management of diabetes in Korean adults: Korea National Health and Nutrition Examination Surveys 1998–2005.
      , Kim et al.
      • Kim S.M.
      • Lee J.S.
      • Lee J.
      • Na J.K.
      • Han J.H.
      • Yoon D.K.
      • et al.
      Prevalence of diabetes and impaired fasting glucose in Korea: Korean National Health and Nutrition Survey 2001.
      TaiwanChang et al.
      • Chang H.-Y.
      • Hsu C.-C.
      • Pan W.-H.
      • Liu W.-L.
      • Cheng J.Y.-C.
      • Tseng C.-H.
      • et al.
      Gender differences in trends in diabetes prevalence from 1993 to 2008 in Taiwan.
      Viet NamNguyen et al.
      • Nguyen Q.N.
      • Pham S.T.
      • Do L.D.
      • Nguyen V.L.
      • Wall S.
      • Weinehall L.
      • et al.
      Cardiovascular disease risk factor patterns and their implications for intervention strategies in Vietnam.
      There were regional differences in the prevalence of diabetes across the seven IDF Regions and by income group (Table 3 and Fig. 1). The highest regional, unadjusted, prevalence was in the North America and Caribbean region (11.0%). However, after age-adjustment the Middle East and North Africa region had the highest prevalence at 10.9%. While the Africa region has the lowest prevalence of adults with diabetes (5.7%), it is projected to have the largest proportional increase in the numbers of adults with diabetes by 2035, with an increase of 109%. All regions are projected to have an increase in the numbers of people with diabetes larger than those projected for growth in the adult population alone. Overall, the numbers of adults with diabetes will increase by 55% by 2035.
      Table 3Diabetes prevalence and number of people with diabetes (20–79 years) by IDF Region for 2013 and 2035.
      Region20132035
      Population (20–79 years)Number of people with diabetes (20–79 years)Comparative diabetes prevalence (20–79 years)Population (20–79 years)Number of people with diabetes (20–79 years)Comparative diabetes prevalence (20–79 years)Increase in the number of people with diabetes
      MillionsMillions%MillionsMillions%%
      AFR407.819.85.7775.541.46.0109.1
      EUR658.756.36.8668.768.97.122.4
      MENA347.534.610.9583.767.911.396.2
      NAC334.936.79.6404.550.412.337.3
      SACA300.524.18.2394.238.58.259.8
      SEA883.272.18.71216.9123.09.470.6
      WP1613.2138.28.11818.2201.88.446.0
      World4572.9381.88.35861.7591.98.855.0
      Figure thumbnail gr1
      Fig. 1Prevalence estimates of diabetes (20–79 years) by income group and age, 2013
      The top ten highest prevalence countries are predominantly Pacific island nations led by Tokelau (Table 4). The other three countries are from the Middle East and North Africa Region: Saudi Arabia, Kuwait, and Qatar. Indeed, many of the countries in the Middle East and North Africa Region have high prevalence rates, well above the global prevalence of 8.3%. In addition, many island nations in the Caribbean, Indian Ocean, and Western Pacific have higher prevalence rates than mainland countries in the same regions.
      Table 4Top 10 countries/territories for prevalence and number of people with diabetes (20–79 years), 2013 and 2035.
      20132035
      Country/territory%Country/territory%
      Top 10 countries/territories for prevalence
      Comparative prevalence.
      (%) of diabetes (20–79 years), 2013 and 2035
      Tokelau37.5Tokelau37.9
      Federated States of Micronesia35.0Federated States of Micronesia35.1
      Marshall Islands34.9Marshall Islands35.0
      Kiribati28.8Kiribati28.9
      Cook Islands25.7Cook Islands25.7
      Vanuatu24.0Saudi Arabia24.5
      Saudi Arabia24.0Vanuatu24.2
      Nauru23.3Nauru23.3
      Kuwait23.1Kuwait23.2
      Qatar22.9Qatar22.8
      20132035
      Country/territoryMillionsCountry/territoryMillions
      Top 10 countries/territories of number of people with diabetes (20–79 years), 2013 and 2035
      China98.4China142.7
      India65.1India109.0
      United States of America24.4United States of America29.7
      Brazil11.9Brazil19.2
      Russian Federation10.9Mexico15.7
      Mexico8.7Indonesia14.1
      Indonesia8.5Egypt13.1
      Germany7.6Pakistan12.8
      Egypt7.5Turkey11.8
      Japan7.2Russian Federation11.1
      a Comparative prevalence.
      Countries with large adult populations are also those with high numbers of people with diabetes. China has the highest number of people with diabetes with over 98.4 million adults affected; this is followed closely by India with 65.1 million. Eight out of the ten most populous countries in the world are also found in the top ten countries with the highest number of adults with diabetes. Only Bangladesh and Nigeria are not in the top ten countries with the highest numbers of people with diabetes (replaced by Mexico and Germany) although these countries are ranked 14 and 16, respectively.
      Diabetes prevalence and numbers of people with diabetes vary substantially by World Bank income group. The vast majority of people with diabetes live in low- and middle-income countries. When seen across income groups, the greatest increases in people with diabetes over the next 20 years will parallel increases in the adult population. However, for every percentage increase in the adult population, the proportional increase in the numbers of people will be greater and especially for developing countries. The greatest proportional increase in the number of adults with diabetes is expected in low-income countries (108%), followed by lower middle-income countries (60%), upper middle-income countries (51%), and finally high-income countries (28%).
      Diabetes prevalence increases with age across all regions and income groups (Fig. 1). The highest age-specific prevalence is in people 60–79 years of age (18.6%), although the largest numbers of people with diabetes are in the 40–59 year age group (184 million). These patterns are expected to persist over the next 20 years. The proportions of adults with diabetes under the age of 50 vary by region and income group with the highest proportion in Africa region (61%) and low-income countries (67%); although there is significant overlap in these figures as most low-income countries are in the Africa region. The greatest proportional increase in the number of people with diabetes by age group is expected to occur in people between 60 and 79 years of age.

      4. Discussion

      The estimates presented here confirm the large and growing burden of diabetes in the world established by previous estimates. There remains considerable variation in the burden of diabetes across regions and income groups with developing countries disproportionately affected. People with diabetes in high-income countries are predominantly over the age of 50 (74%) while those in low- and middle-income countries are mostly under the age of 50 (59%). Particularly for developing countries, demographic patterns are expected to change substantially over the next generations with increases in life expectancy, decreases in the infectious disease burden, and higher rates of urbanisation. These changes will also drive increases in diabetes prevalence in those countries.
      Fig. 1 presents the age-specific prevalence of diabetes when divided by income group and shows a much lower prevalence of diabetes in older adults in low-income countries, compared to higher income countries. This may be a result of a number of factors including: higher mortality in people with diabetes in these countries, or a cohort effect whereby it is younger people developing diabetes. As life expectancy increases, we can expect to see greater numbers of adults with diabetes living longer in these countries which will drive the large proportional increases for low- and middle-income countries over the next generation. In addition, the higher prevalence of diabetes among younger adults in lower and upper middle-income countries will also drive increases as those people age, countries develop, and life expectancy increases. Without concomitant improvements in the health system for early detection and treatment, the rates of complications and deaths due to diabetes can also be expected to increase substantially in these countries. Until prevention and awareness of the disease improves, we cannot expect to see a shift in the curves for low- and middle-income countries towards a decrease in prevalence for younger age groups like that seen for high-income countries.
      The IDF approach to estimating diabetes prevalence is simple, reproducible, and intentionally conservative. Prevalence estimates for 2013 are derived from the most recent available data with an effort made to minimise extrapolation and use the available evidence to inform the assumptions applied. The estimates are greatly affected by changes in the underlying data. For example, estimates of diabetes in Turkey have increased from previous estimates due to the inclusion of data from the TURDEP-II study [
      • Satman I.
      • Omer B.
      • Tutuncu Y.
      • Kalaca S.
      • Gedik S.
      • Dinccag N.
      • et al.
      Twelve-year trends in the prevalence and risk factors of diabetes and prediabetes in Turkish adults.
      ] showing a prevalence of 16.5%; an increase from the 11.4% estimate from the previous study. Similarly, a new study on the prevalence of diabetes in China published in the Journal of the America Medical Association [
      • Xu Y.
      • Wang L.
      • He J.
      • Bi Y.
      • Li M.
      • Wang T.
      • et al.
      Prevalence and control of diabetes in Chinese adults.
      ] after the estimates presented here were calculated showed a prevalence of 11.6%, which, if selected for future estimates, would likely increase the prevalence estimate in that country and countries dependent on the data for extrapolation.
      Global estimates of diabetes prevalence have shown increases over the past 15 years. The latest estimates surpass projections made by previous estimates. In 1998, King et al. projected that the number of adults with diabetes would reach 300 million by 2025 [
      • King H.
      • Aubert R.E.
      • Herman W.H.
      Global burden of diabetes, 1995–2025: prevalence, numerical estimates, and projections.
      ]; and in 2004, the WHO estimated that by 2030 the number would exceed 366 million [
      • Wild S.
      • Roglic G.
      • Green A.
      • Sicree R.
      • King H.
      Global prevalence of diabetes: estimates for the year 2000 and projections for 2030.
      ]. In addition, the IDF estimated a global prevalence of 151 million in 2000 [
      Diabetes Atlas.
      ]; 194 million in 2003 [
      Diabetes Atlas.
      ]; 246 million in 2006 [
      Diabetes Atlas.
      ]; 285 million in 2010 [
      • Shaw J.E.
      • Sicree R.A.
      • Zimmet P.Z.
      Global estimates of the prevalence of diabetes for 2010 and 2030.
      ]; and most recently, 366 million in 2011 [
      • Whiting D.R.
      • Guariguata L.
      • Weil C.
      • Shaw J.
      IDF Diabetes Atlas: global estimates of the prevalence of diabetes for 2011 and 2030.
      ]. All of these estimates have been surpassed by the estimate in this paper of 382 million in 2013 and we can expect that the projections presented here are likely also to be an underestimate. Each estimate has been based on the latest and highest quality data available. While the methodology has changed and been adapted as more information has become available, the increases seen are likely due to increases in incidence reflected in the availability of newer data reporting increasing prevalence of diabetes. Some increases in prevalence could also be a result of decreases in diabetes mortality where health systems are preventing deaths from complications; however the evidence for this is lacking.
      The estimates are also particularly sensitive to the data underlying the assumptions applied to estimate undiagnosed diabetes. As discussed at length in Beagley et al. [
      • Beagley J.
      • Guariguata L.
      • Weil C.
      • Motala A.A.
      Global estimates of undiagnosed diabetes in adults.
      ], undiagnosed diabetes is particularly sensitive to the performance of the health system and not to the underlying biology of diabetes. Thus, sampling frames and grouping of countries for extrapolation can have a profound effect on the pooled proportion of undiagnosed diabetes applied to a country. The recent study from China [
      • Xu Y.
      • Wang L.
      • He J.
      • Bi Y.
      • Li M.
      • Wang T.
      • et al.
      Prevalence and control of diabetes in Chinese adults.
      ] also reported a much higher proportion (70%) of undiagnosed diabetes than previous studies in the same country, which, if included in the future, could have repercussions for estimates in the region.
      Changes in the classification of countries used for extrapolation are also likely to have an effect on the way the estimates are calculated. For instance, since the generation of these estimates, the World Bank has reclassified a number of countries into new income group categories [

      World Bank. Country and Lending Groups, Available from: http://data.worldbank.org/about/countryclassifications/country-and-lending-groups [cited 17.09.13].[Internet].

      ]. Most notably, the Russian Federation has now been classified as high-income. Because of the way countries are grouped for extrapolation, and the size of the population in the Russian Federation, this shift is likely to have a substantial effect on future estimates.
      The modelling approach used here takes into account only changes in the population and urbanisation for the calculation of the 2035 projections and presents a conservative estimate of the prevalence of diabetes. Thus, increases in obesity and other risk factors for diabetes could drive the prevalence even higher over the next 20 years.
      There are more high quality, population-based studies of diabetes available than ever before. For the estimates presented here, 744 data sources were considered and 174 included representing 130 countries. Of those studies, 142 were nationally representative, 69 were based on fasting blood glucose values, and 55 were based on OGTT. There is some regional variability in the availability of high quality data and the Africa region had lowest proportion of countries with original data of sufficient quality for inclusion.
      Nationally representative studies are particularly important for high population countries within which regional variability may be considerable. The availability of large, nationally representative, recent studies for India and China, and high quality routine data collection in Mexico, Australia, the United States and Canada, translate to more stability and a higher confidence in the estimates for those countries. However, there is a considerable lack of population-based surveys based on fasting blood glucose or OGTT in high-income countries where self-reported surveys are abundant. This has a particular impact on the estimation of undiagnosed diabetes which leads to more uncertainty in the estimates for those countries.
      In conclusion, while it is clear that the availability of more high-quality data is essential to improve the certainty around the estimates of diabetes prevalence, the latest evidence shows that diabetes continues to be a large and increasing global health burden and is likely to continue to grow substantially in the next decades. Increases in diabetes prevalence are driven by rapid development and subsequent changes in lifestyle. Coupled with the comparatively slow development of health systems, diabetes and its complications will continue to be an especially high burden in low- and middle-income countries.

      Conflict of interest

      The authors have no conflicts of interest to disclose.

      Acknowledgements

      The authors would like to acknowledge the contribution of the IDF Diabetes Atlas committee and in particular Professor Nam Han Cho, chair of the committee, in the generation of the estimates presented here.
      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.

      Appendix A. Supplementary data

      The following are the supplementary data to this article:

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