Goodarz DanaeiSaman FahimiYuan LuBin ZhouKaveh HajifathalianMariachiara Di CesareWei Cheng LoBarbara Reis-SantosMelanie J. CowanJonathan E. ShawJames BenthamJohn K. LinHonor BixbyDianna MaglianoPascal BovetJ. Jaime MirandaYoung Ho KhangGretchen A. StevensLeanne M. RileyMohammed K. AliMajid EzzatiKhalid Abdul KadirNiveen M. Abu-RmeilehBenjamin Acosta-CazaresWichai AekplakornCarlos A. Aguilar-SalinasAlireza AhmadvandMohannad Al NsourAla'a AlkerwiPhilippe AmouyelLars Bo AndersenSigmund A. AnderssenDolores S. AndradeRanjit Mohan AnjanaHajer Aounallah-SkhiriTahir ArisNimmathota ArlappaDominique ArveilerFelix K. AssahMária AvdicováNagalla BalakrishnaPiotr BandoszCarlo M. BarbagalloAlberto BarcelóAnwar M. BatiehaLouise A. BaurHabiba Ben RomdhaneAntonio Bernabe-OrtizSantosh K. BhargavaYufang BiPeter BjerregaardCecilia BjörkelundMargaret BlakeAnneke BlokstraSimona BoBernhard O. BoehmCarlos P. BoissonnetImperia BrajkovichJuergen BreckenkampLizzy M. BrewsterGarry R. BrianGraziella BrunoAnna BuggeAntonio Cabrera de LeónGunay CanAna Paula C. CândidoVincenzo CapuanoMaria J. CarvalhoFelipe F. CasanuevaCarmelo A. CasertaKatia CastetbonSnehalatha ChamukuttanNishi ChaturvediChien Jen ChenFangfang ChenShuohua ChenChing Yu ChengAngela ChetritShu Ti ChiouYumi ChoJerzy ChudekRenata CifkovaFrank ClaessensHans ConcinCyrus CooperRachel CooperSimona CostanzoDominique CottelChris CowellAna B. CrujeirasGraziella D'ArrigoJean DallongevilleRachel DanknerLuc DauchetGiovanni de GaetanoStefaan de HenauwMohan DeepaAbbas DehghanHarvard School of Public HealthImperial College LondonNational Taiwan UniversityUniversidade Federal de PelotasOrganisation Mondiale de la SanteBaker Heart and Diabetes InstituteUniversity of California, San FranciscoUniversitat Lausanne SchweizUniversidad Peruana Cayetano HerediaSeoul National UniversityEmory UniversityMonash University MalaysiaBirzeit UniversityInstituto Mexicano del Seguro SocialMahidol UniversityInstituto Nacional de la Nutricion Salvador ZubiranTehran University of Medical SciencesEastern Mediterranean Public Health NetworkLuxembourg Institute of HealthUniversity of LilleSyddansk UniversitetNorges idrettshogskoleUniversity of CuencaMadras Diabetes Research FoundationNational Institute of Public HealthKementerian Kesihatan MalaysiaIndian Council of Medical ResearchStrasbourg University and HospitalHealth of Population in Transition Research Group (HoPiT)Regional Authority of Public HealthGdanski Uniwersytet MedycznyUniversita degli Studi di PalermoPan American Health OrganizationJordan University of Science and TechnologyThe University of SydneyUniversity of Tunis El ManarSunder Lal Jain HospitalShanghai Jiao Tong University School of MedicineGoteborgs UniversitetNatCen Social ResearchNational Institute of Public Health and the EnvironmentUniversita degli Studi di TorinoNanyang Technological UniversityCentro de Educación Médica e Investigaciones ClínicasUniversidad Central de VenezuelaUniversitat BielefeldUniversity of AmsterdamFred Hollows Foundation, New ZealandCanarian Health ServiceIstanbul UniversitesiReparto di Cardiologia ed UTIC di Mercato S.Universidade do PortoUniversidad de Santiago de CompostelaAssociazione Calabrese di EpatologiaFrench Institute for Health SurveillanceIndia Diabetes Research FoundationUCLAcademia Sinica TaiwanCapital Institute of PediatricsKailuan General HospitalDuke-NUS Medical School SingaporeThe Gertner InstituteMinistry of Health and WelfareKorea Centers for Disease Control & PreventionSlaski Uniwersytet Medyczny w KatowicachCharles UniversityKU LeuvenAgency for PreventiveUniversity of SouthamptonIRCCS Istituto Neurologico Mediterraneo NeuromedInstitut Pasteur LilleCIBERobnConsiglio Nazionale delle RicercheCentre Hospitalier Regional Universitaire de LilleUniversiteit GentErasmus University Medical CenterMinistry of Health SeychellesUniversity of Greenland2018-11-232018-11-232015-08-01The Lancet Diabetes and Endocrinology. Vol.3, No.8 (2015), 624-63722138595221385872-s2.0-84938199196https://repository.li.mahidol.ac.th/handle/20.500.14594/35418© 2015 NCD Risk Factor Collaboration. Background: Diabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose tolerance test (2hOGTT), and HbA1c. We assessed the effect of different diagnostic definitions on both the population prevalence of diabetes and the classification of previously undiagnosed individuals as having diabetes versus not having diabetes in a pooled analysis of data from population-based health examination surveys in different regions. Methods: We used data from 96 population-based health examination surveys that had measured at least two of the biomarkers used for defining diabetes. Diabetes was defined using HbA1c (HbA1c ≥6·5% or history of diabetes diagnosis or using insulin or oral hypoglycaemic drugs) compared with either FPG only or FPG-or-2hOGTT definitions (FPG ≥7·0 mmol/L or 2hOGTT ≥11·1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated diabetes prevalence, taking into account complex survey design and survey sample weights. We compared the prevalences of diabetes using different definitions graphically and by regression analyses. We calculated sensitivity and specificity of diabetes diagnosis based on HbA1c compared with diagnosis based on glucose among previously undiagnosed individuals (ie, excluding those with history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated sensitivity and specificity in each survey, and then pooled results using a random-effects model. We assessed the sources of heterogeneity of sensitivity by meta-regressions for study characteristics selected a priori. Findings: Population prevalence of diabetes based on FPG-or-2hOGTT was correlated with prevalence based on FPG alone (r=0·98), but was higher by 2-6 percentage points at different prevalence levels. Prevalence based on HbA1c was lower than prevalence based on FPG in 42·8% of age-sex-survey groups and higher in another 41·6%; in the other 15·6%, the two definitions provided similar prevalence estimates. The variation across studies in the relation between glucose-based and HbA1c-based prevalences was partly related to participants' age, followed by natural logarithm of per person gross domestic product, the year of survey, mean BMI, and whether the survey population was national, subnational, or from specific communities. Diabetes defined as HbA1c 6·5% or more had a pooled sensitivity of 52·8% (95% CI 51·3-54·3%) and a pooled specificity of 99·74% (99·71-99·78%) compared with FPG 7·0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes defined based on FPG-or-2hOGTT was 30·5% (28·7-32·3%). None of the preselected study-level characteristics explained the heterogeneity in the sensitivity of HbA1c versus FPG. Interpretation: Different biomarkers and definitions for diabetes can provide different estimates of population prevalence of diabetes, and differentially identify people without previous diagnosis as having diabetes. Using an HbA1c-based definition alone in health surveys will not identify a substantial proportion of previously undiagnosed people who would be considered as having diabetes using a glucose-based test.Mahidol UniversityBiochemistry, Genetics and Molecular BiologyMedicineArticleSCOPUS10.1016/S2213-8587(15)00129-1