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The IDF Diabetes Atlas methodology for estimating global prevalence of hyperglycaemia in pregnancy

Published:December 03, 2013DOI:https://doi.org/10.1016/j.diabres.2013.11.004

      Abstract

      Introduction

      Hyperglycaemia is one of the most prevalent metabolic disorders occurring during pregnancy. Limited data are available on the global prevalence of hyperglycaemia in pregnancy. The International Diabetes Federation (IDF) has developed a methodology for generating estimates of the prevalence of hyperglycaemia in pregnancy, including hyperglycaemia first detected in pregnancy and live births to women with known diabetes, among women of childbearing age (20–49 years).

      Methods

      A systematic review of the literature for studies reporting the prevalence of gestational diabetes was conducted. Studies were evaluated and scored to favour those that were representative of a large population, conducted recently, reported age-specific estimates, and case identification was based on blood test. Age-specific prevalence data from studies were entered to produce estimates for five-year age groups using logistic regression to smooth curves, with age as the independent variable. The derived age-specific prevalence was adjusted for differences in diagnostic criteria in the underlying data. Cases of hyperglycaemia in pregnancy were derived from age-specific estimates of fertility and age-specific population estimates. Country-specific estimates were generated for countries with available data. Regional and global estimates were generated based on aggregation and extrapolation for 219 countries and territories. Available fertility rates and diabetes prevalence estimates were used to estimate the proportion of hyperglycaemia in pregnancy that may be due to total diabetes in pregnancy – pregnancy in women with known diabetes and diabetes first detected in pregnancy.

      Results

      The literature review identified 199 studies that were eligible for characterisation and selection. After scoring and exclusion requirements, 46 studies were selected representing 34 countries. More than 50% of selected studies came from Europe and North America and Caribbean. The smallest number of identified studies came from sub-Saharan Africa. The majority of studies were for high-income countries, although low- and middle-income countries were also represented.

      Conclusion

      Prevalence estimates of hyperglycaemia in pregnancy are sensitive to the data from which they are derived. The IDF methodology is a transparent, reproducible, and modifiable method for estimating the burden of hyperglycaemia in pregnancy. More data are needed, in particular from developing countries, to strengthen the methodology.

      Keywords

      1. Introduction

      The World Health Organization (WHO) recently published a new definition for hyperglycaemia first detected in pregnancy (HFDP) which includes both gestational diabetes mellitus (GDM) and diabetes mellitus in pregnancy (DIP) [
      • World Health Organization
      Diagnostic criteria and classification of hyperlgycaemia first detected in pregnancy.
      ]. GDM was previously defined as “glucose intolerance with onset or first recognition in pregnancy” or “carbohydrate intolerance of varying severity which is diagnosed in pregnancy and may or may not resolve after pregnancy” [
      • Negrato C.A.
      • Gomes M.B.
      Historical facts of screening and diagnosing diabetes in pregnancy.
      ]. During the 2nd International Workshop on GDM in October 1984 it was added that “the definition applies irrespective of whether or not insulin is used for the treatment or if the condition persists after pregnancy” [
      • Negrato C.A.
      • Gomes M.B.
      Historical facts of screening and diagnosing diabetes in pregnancy.
      ]. Early definitions of GDM did not differentiate between diabetes that existed before, or after the pregnancy and hyperglycaemia that resolved postnatally. The growing burden of type 2 diabetes mellitus (T2DM) in women of reproductive age has driven the need for the new definition put forth by the WHO which also takes into account the unique care needs of different degrees of hyperglycaemia first detected in pregnancy (HFDP) [
      • Metzger B.E.
      • Coustan D.R.
      The Organizing Committee
      ,
      • American Diabetes Association
      Gestational diabetes mellitus.
      ]. Total diabetes in pregnancy (TDP) incorporates, in addition to DIP, women with known diabetes who may be pregnant.
      Hyperglycaemia in Pregnancy (HIP), including women with HFDP and TDP (Fig. 1), is a common metabolic disorder during pregnancy, is associated with serious complications for mother and child. HIP has been associated with leading causes of maternal mortality including: post partum haemorrhage, hypertensive disorders, obstructed labour, caesarean section and sepsis [
      • Veeraswamy S.
      • Vijayam B.
      • Gupta V.K.
      • Kapur A.
      Gestational diabetes: the public health relevance and approach.
      ]. It is associated with serious risks for mother and child that include preeclampsia, obstructed labour, and infant macrosomia [
      • Veeraswamy S.
      • Vijayam B.
      • Gupta V.K.
      • Kapur A.
      Gestational diabetes: the public health relevance and approach.
      ,
      • Nikoo M.K.
      • Ahranjani S.A.
      • Larijani B.
      A review on the prevalence of gestational diabetes mellitus (GDM) in different regions of Iran.
      ]. Studies which previously reported the prevalence of GDM would now be classified under the new definition as reporting HFDP as those studies made no distinction between GDM and DIP. The complications associated with HFDP are similar to those associated with GDM. The principal difference is that women with GDM are more susceptible to subsequently develop T2DM later in life and women with DIP are more likely to suffer serious complications during pregnancy [
      • American Diabetes Association
      Gestational diabetes mellitus.
      ,
      • Veeraswamy S.
      • Vijayam B.
      • Gupta V.K.
      • Kapur A.
      Gestational diabetes: the public health relevance and approach.
      ,
      • Wahabi H.A.
      • Esmaeil S.A.
      • Fayed A.
      • Al-Shaikh G.
      • Alzeidan R.A.
      Pre-existing diabetes mellitus and adverse pregnancy outcomes.
      ].
      Figure thumbnail gr1
      Fig. 1Terminology and classification for estimates of hyperglycaemia in pregnancy.
      Various national and international bodies have published a range of guidelines and recommendations on screening methods and diagnostic criteria for the screening and diagnosis of HFDP (now classified under the new WHO definition, previously termed GDM). These recommendations differ in their requirement for the subject to be in a fasting state, the number of appointments needed, the amount of glucose administered and blood glucose thresholds for case identification. Depending on which criteria and screening method are applied (Fig. 2); the resulting reported prevalence can vary widely. This variation poses a serious problem when trying to compare prevalence figures across studies.
      Figure thumbnail gr2
      Fig. 2Diagnostic and screening methods currently in use for estimating gestational diabetes and hyperglycaemia first-detected during pregnancy.
      Due to a substantial heterogeneity in screening methods and diagnostic criteria for what has traditionally been termed GDM and would now be considered HFDP, the global burden of HIP has yet to be rigorously quantified. Consequently, the International Diabetes Federation (IDF) has developed a methodology to systematically estimate the global prevalence of HIP among women of reproductive age (20–49 years).

      2. Methods

      Fig. 3 provides an overview of the methodology described below [
      • United Nations, Department of Economic and Social Affairs, Population Division
      ,
      • IDF
      Diabetes Atlas.
      ].
      Figure thumbnail gr3
      Fig. 3IDF methodology for estimating hyperglycaemia in pregnancy.

      2.1 Literature search

      A systematic literature search of PubMed, Google Scholar, relevant citations from within papers, and gathered information from experts and researchers in the IDF network was conducted from February 2013 to April 2013 to identify studies reporting the prevalence of GDM using the terms: ‘gestational diabetes mellitus’, ‘GDM’, ‘prevalence’, ‘incidence’ and ‘screening’ and <country name> or <region/continent>. The term “gestational diabetes” and associated terms listed above were used to identify studies.
      Data were entered and stored in a MySQL database with an OpenOffice Base data-entry system. Data management and statistical programming were conducted using the R Project for Statistical Computing version 2.15.2 (www.r-project.org) [
      • R Development Core Team
      R: a language and environment for statistical computing.
      ]. For each data source, the country, title, abstract, authors, PubMed ID, and publication year were stored in the database. In addition, fields characterising the study were stored as shown in Table 1.
      Table 1Study characterisation fields.
      FieldOptionsDescription
      Sample representationSingle hospitalStudy carried out in a single hospital
      LocalStudy carried out in one city
      Multi-cityStudy carried out in multiple cities
      RegionalStudy carried out on regional level
      NationalStudy carried out on national level
      Study designPopulation-basedThe sample was taken systematically from the entire population in a given area
      Cohort studyThe sample was taken from a cohort not representative of the entire population
      ModellingResults based on modelling from a number of data sources combined through meta-analysis or similar pooling
      Sample sizeNumber of the total sample sizeThe sample size used for the entire study
      Study dateYearThe year in which the study was conducted
      Screening-week<24Screening was performed exclusively before 24th week of gestation
      24–28Screening was performed between week 24 and 28 of gestation
      >28Screening was performed exclusively after 28th week of gestation
      MultipleScreening was performed multiple times during gestation
      Not availableAuthors did not indicate when the screening was performed
      Diagnostic criteriaADAAmerican Diabetes Association criteria (2000–2010)
      ADIPSAustralasian Diabetes in Pregnancy Study Group criteria
      CDACanadian Diabetes Association criteria
      EASDEuropean Association for the study of Diabetes criteria
      IADPSGInternational Association of the Diabetes and Pregnancy Study Groups criteria (including ADA criteria from 2011)
      ICD-classificationInternational Classification of Diseases tool
      NDDG (ADA < 2000)National Diabetes Data Group criteria (including ADA prior to 2000)
      WHOWorld Health Organization criteria (1985 and 1999)

      2.2 Exclusion criteria

      Study information was stored for all sources, however studies were excluded from further analysis if one or more of the following characteristics were applicable: data were duplicated or published in multiple papers (only the most complete data were stored), study was conducted prior to 1980, a non-representative sample of the general population (e.g. a single ethnic group, a single insurance provider, study only in migrants, etc.), exclusive focus on multi-parity, screening was carried out exclusively before the 24th week of gestation, less than three age groups for age-specific estimates were reported, prevalence reported was a cumulative result of various screening methods, or a lack of clarity on methodology or insufficient data for characterisation. Whether or not risk factor screening has been used during the course of the study was recorded but not part of the selection process.

      2.3 Study characterisation and selection

      Studies were characterised according to sample size, diagnostic criteria, representativeness, and year the study was conducted. In order to simplify characterisation, certain criteria were grouped together. Studies that used either the WHO diagnostic criteria established in 1985 or from 1999 were grouped together as the difference in the diagnostic values was not found to substantially impact the prevalence [
      Diabetes mellitus. Report of a WHO Study Group.
      ,
      • Alberti K.G.
      • Zimmet P.Z.
      Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1. Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.
      ]. Studies using the ADA diagnostic criteria defined prior to 2000 were classified as using the NDDG diagnostic criteria, due to the similarity of these two sets of criteria [
      • American Diabetes Association
      Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus.
      ]. If the ADA diagnostic criteria between 2000 and 2010 were used, studies were classified as using the ADA diagnostic criteria [
      • Carpenter M.W.
      • Coustan D.R.
      Criteria for screening tests for gestational diabetes.
      ,
      Diagnosis and Classification of Diabetes Mellitus.
      ]. However, studies reporting using ADA diagnostic criteria defined in 2011, were classified as IADPSG criteria, due to the similarity of these two sets of criteria [
      • International Association of Diabetes and Pregnancy Study Group Consensus Panel
      International Association of Diabetes and Pregnancy Study Groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy.
      ]. Data sources were carefully reviewed to ensure correct classification of diagnostic criteria.
      A scoring system was developed to weight and select the most appropriate studies to produce prevalence estimates for HIP. Table 2 summarises the study characteristics considered for scoring and the assigned points. The maximum score a study could obtain was seven. Studies with a score of three or less points were excluded.
      Table 2Scoring system for studies reporting prevalence of hyperglycaemia first-detected in pregnancy.
      DomainItemValue
      Diagnostic criteriaRecord-based/self-reported0
      Criteria-based1
      Study year<20000
      −20051
      >20052
      Study designModelling based on pooled or extrapolated data0
      Population-based/universal consecutive pregnancy screening1
      RepresentationSingle-hospital0
      Local1
      Multi-city1
      Regional2
      National3

      2.4 Statistical methods

      2.4.1 Logistic regression

      Age-specific prevalence for HFDP was derived from the selected prevalence studies. Age-specific data from studies were entered to produce estimates for five year age groups [
      • McElduff A.
      • Cheung N.W.
      • McIntyre H.D.
      • Lagström J.A.
      • Oats J.J.N.
      • Ross G.P.
      • et al.
      The Australasian Diabetes in Pregnancy Society consensus guidelines for the management of type 1 and type 2 diabetes in relation to pregnancy.
      ,
      • Canadian Diabetes Association Clinical Practice Guidelines Expert Committee
      Canadian Diabetes Association 2008 clinical practice guidelines for the prevention and management of diabetes in Canada.
      ,
      Diabetes mellitus. Report of a WHO Study Group.
      ,
      • Alberti K.G.
      • Zimmet P.Z.
      Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1. Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.
      ,
      • Metzger B.E.
      • Gabbe S.G.
      • Persson B.
      • Buchanan T.A.
      • Catalano P.M.
      • et al.
      International Association of Diabetes & Pregnancy Study Groups (IADPSG) Consensus Panel Writing Group and the Hyperglycemia & Adverse Pregnancy Outcome (HAPO) Study Steering Committee
      The diagnosis of gestational diabetes mellitus: new paradigms or status quo?.
      ,
      • American Diabetes Association
      Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus.
      ,
      • Carpenter M.W.
      • Coustan D.R.
      Criteria for screening tests for gestational diabetes.
      ,
      Diagnosis and Classification of Diabetes Mellitus.
      ,
      • International Association of Diabetes and Pregnancy Study Group Consensus Panel
      International Association of Diabetes and Pregnancy Study Groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy.
      ,
      • Benhalima K.
      • Hanssens M.
      • Devlieger R.
      • Verhaeghe J.
      • Mathieu C.
      Analysis of pregnancy outcomes using the New IADPSG recommendation compared with the Carpenter and Coustan Criteria in an area with a low prevalence of gestational diabetes.
      ,
      • Shirazian N.
      • Emdadi R.
      • Mahboubi M.
      • Motevallian A.
      • Fazel-Sarjuei Z.
      • Sedighpour N.
      • et al.
      Screening for gestational diabetes: usefulness of clinical risk factors.
      ,
      • Bener A.
      • Saleh N.M.
      • Al-Hamaq A.
      Prevalence of gestational diabetes and associated maternal and neonatal complications in a fast-developing community: global comparisons.
      ,
      • Agarwal M.M.
      • Dhatt G.S.
      • Shah S.M.
      Gestational diabetes mellitus: simplifying the international association of diabetes and pregnancy diagnostic algorithm using fasting plasma glucose.
      ,
      • Feig D.S.
      • Shah B.R.
      • Lipscombe L.L.
      • Wu C.F.
      • Ray J.G.
      • Lowe J.
      • et al.
      Preeclampsia as a risk factor for diabetes: a population-based cohort study.
      ,
      • Liu S.L.
      • Shah B.R.
      • Naqshbandi M.
      • Tran V.
      • Harris S.B.
      Increased rates of adverse outcomes for gestational diabetes and pre-pregnancy diabetes in on-reserve First Nations Women in Ontario, Canada.
      ] using logistic regression to smooth the curves, with age (midpoint of each age group) as the independent variable. The final binary logistic formula was as follows:
      Y=β0+β1Xage


      where Y is the prevalence, β0 is the intercept and Xage is the midpoint of the age group. Age-specific prevalence across five-year age groups [
      • McElduff A.
      • Cheung N.W.
      • McIntyre H.D.
      • Lagström J.A.
      • Oats J.J.N.
      • Ross G.P.
      • et al.
      The Australasian Diabetes in Pregnancy Society consensus guidelines for the management of type 1 and type 2 diabetes in relation to pregnancy.
      ,
      • Canadian Diabetes Association Clinical Practice Guidelines Expert Committee
      Canadian Diabetes Association 2008 clinical practice guidelines for the prevention and management of diabetes in Canada.
      ,
      Diabetes mellitus. Report of a WHO Study Group.
      ,
      • Alberti K.G.
      • Zimmet P.Z.
      Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1. Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.
      ,
      • Metzger B.E.
      • Gabbe S.G.
      • Persson B.
      • Buchanan T.A.
      • Catalano P.M.
      • et al.
      International Association of Diabetes & Pregnancy Study Groups (IADPSG) Consensus Panel Writing Group and the Hyperglycemia & Adverse Pregnancy Outcome (HAPO) Study Steering Committee
      The diagnosis of gestational diabetes mellitus: new paradigms or status quo?.
      ,
      • American Diabetes Association
      Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus.
      ,
      • Carpenter M.W.
      • Coustan D.R.
      Criteria for screening tests for gestational diabetes.
      ,
      Diagnosis and Classification of Diabetes Mellitus.
      ,
      • International Association of Diabetes and Pregnancy Study Group Consensus Panel
      International Association of Diabetes and Pregnancy Study Groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy.
      ,
      • Benhalima K.
      • Hanssens M.
      • Devlieger R.
      • Verhaeghe J.
      • Mathieu C.
      Analysis of pregnancy outcomes using the New IADPSG recommendation compared with the Carpenter and Coustan Criteria in an area with a low prevalence of gestational diabetes.
      ,
      • Shirazian N.
      • Emdadi R.
      • Mahboubi M.
      • Motevallian A.
      • Fazel-Sarjuei Z.
      • Sedighpour N.
      • et al.
      Screening for gestational diabetes: usefulness of clinical risk factors.
      ,
      • Bener A.
      • Saleh N.M.
      • Al-Hamaq A.
      Prevalence of gestational diabetes and associated maternal and neonatal complications in a fast-developing community: global comparisons.
      ,
      • Agarwal M.M.
      • Dhatt G.S.
      • Shah S.M.
      Gestational diabetes mellitus: simplifying the international association of diabetes and pregnancy diagnostic algorithm using fasting plasma glucose.
      ,
      • Feig D.S.
      • Shah B.R.
      • Lipscombe L.L.
      • Wu C.F.
      • Ray J.G.
      • Lowe J.
      • et al.
      Preeclampsia as a risk factor for diabetes: a population-based cohort study.
      ,
      • Liu S.L.
      • Shah B.R.
      • Naqshbandi M.
      • Tran V.
      • Harris S.B.
      Increased rates of adverse outcomes for gestational diabetes and pre-pregnancy diabetes in on-reserve First Nations Women in Ontario, Canada.
      ] was calculated using the “predict” function in R.

      2.5 Adjustment for diagnostic criteria

      The derived age-specific prevalence was adjusted for the specific diagnostic criteria for HFDP in each study. Adjusting for the different criteria involved two steps:
      • (1)
        The prevalence of any study that used any diagnostic criteria other than the one proposed by IADPSG or WHO 1999 were doubled in accordance with published research comparing various diagnostic methods [
        • Benhalima K.
        • Hanssens M.
        • Devlieger R.
        • Verhaeghe J.
        • Mathieu C.
        Analysis of pregnancy outcomes using the New IADPSG recommendation compared with the Carpenter and Coustan Criteria in an area with a low prevalence of gestational diabetes.
        ,
        • Santos-Ayarzagoitia M.
        • Salinas-Martínez A.M.
        • Villarreal-Pérez J.Z.
        Gestational diabetes: validity of ADA and WHO diagnostic criteria using NDDG as the reference test.
        ].
      • (2)
        All studies that based their prevalence on the WHO 1999 criteria were scaled up by 30% as an adjustment for the higher glucose threshold used by that criteria [
        • O'Sullivan E.P.
        • Avalos G.
        • O’Reilly M.
        • Dennedy M.C.
        • Gaffney G.
        • Dunne F.
        Atlantic Diabetes in Pregnancy (DIP): the prevalence and outcomes of gestational diabetes mellitus using new diagnostic criteria.
        ]. Studies using the IADPSG criteria were not scaled. Studies based on ICD classification were not scaled.
      No adjustment was made to studies using different diagnostic values for blood glucose or different glycaemic loads, as the evidence does not support a significant difference in the prevalence when adopting different values.

      2.6 Country-specific estimates

      Country-specific estimates were generated if primary data were available. For each country with available studies, the highest scoring study was selected. If more than one study was selected for a country, the age-specific prevalence results were averaged to produce a country estimate.

      2.7 Calculation of cases and total diabetes in pregnancy

      The number of live births in each country were calculated by applying the age-specific fertility rates from the UN Populations Prospects 2012 to the age-specific population of women derived from the same source [
      • United Nations, Department of Economic and Social Affairs, Population Division
      ]. The criteria-adjusted age-specific prevalence of HFDP was then multiplied by the expected number of live births per country to obtain the expected number of live births in women with HFDP per country.
      We assumed that women with diabetes have the same fertility as women without diabetes. Using age- and sex-specific prevalence of diabetes for women 20–49 from the 6th edition of the IDF Diabetes Atlas [
      • Guariguata L.
      • Whiting D.R.
      • Beagley J.
      • Linnenkamp U.
      • Hambleton I.
      • Cho N.H.
      • et al.
      Global estimates of diabetes prevalence for 2013 and projections for 2035.
      ], the number of live births in women with known diabetes were estimated by multiplying the age-specific estimated number of women with known diabetes to age-specific estimates of fertility [
      • United Nations, Department of Economic and Social Affairs, Population Division
      ].

      2.8 Estimate of HIP and proportion due to TDP

      To estimate overall HIP, which includes HFDP (a combination of DIP and GDM – Fig. 1), the estimated live births among women with known diabetes were added to the estimated cases of HFDP calculated above.
      Fig. 3 gives an overview of the calculations used to arrive at the estimates. Some proportion of HFDP may be a result of previously undiagnosed T2DM (Fig. 1). However, the underlying studies used to generate the estimates do not take into account the new distinction in the definition and thus we were not able to directly extract what proportion of the estimate of HFDP may be due to DIP. This uncertainty is further extended to the estimates of HIP as HFDP makes up a substantial proportion. In order to understand what proportion of the overall HIP estimate may be due to live births in women with known diabetes and women with diabetes first detected in pregnancy (termed total diabetes in pregnancy (TDP)), age-specific estimates of all diabetes [
      • Beagley J.
      • Guariguata L.
      • Weil C.
      • Motala A.A.
      Global estimates of undiagnosed diabetes in adults.
      ] in women were multiplied by age-specific fertility rates to get the number of live births in women with diabetes both known and previously undiagnosed for 2013. This figure was considered to represent cases of TDP and would include a proportion of DIP, which is included in the underlying studies, as well as estimates of live births in women with known diabetes. The total number of live births affected by TDP was divided by the estimated cases of HIP to get the proportion of HIP which may be due to TDP.

      2.9 Regional and global estimates

      Country-specific estimates were generated for countries that had available prevalence data (Table 4).
      Regional and global estimates were generated based on aggregation and extrapolation of the available data. Estimates were generated based on ‘data regions’. A data region was defined as a combination of IDF Region, World Bank country income group as classified in April 2013 [] and matched by ethnicity. If no primary data were available for a data region, the estimates were based on the most appropriate data region with available data. The global estimate was derived by aggregating cases at the regional level and applying the average prevalence rate from available countries to other countries without data in the same data region.

      2.10 Results of the literature search

      The prevalence estimates of HIP that were generated using the above described methodology are described in detail in the publication by Guariguata et al. [
      • Guariguata L.
      • Linnenkamp U.
      • Beagley J.
      • Whiting D.R.
      • Cho N.H.
      Global estimates of the prevalence of hyperglycaemia in pregnancy.
      ]. The search for data identified 199 studies matching the search criteria. These included 197 peer-reviewed publications from scientific journals and two national health surveys. After applying the exclusion criteria, 92 of the 199 studies were eligible for characterisation and selection. After scoring, 46 of the 92 studies were selected representing 36 countries and were used to generate the estimates of prevalence of HIP. Table 3 displays the characteristics of the selected studies.
      Table 3Studies selected for generating the global estimates of HIP.
      Country (study)YearSample sizeSampling frameDiagnostic criteriaStudy prevalence of HFDP (%)Study score
      Africa
       Nigeria
      • Kuti M.A.
      • Abbiyesuku F.M.
      • Akinlade K.S.
      • Akinosun O.M.
      • Adedapo K.S.
      • Adeleye J.O.
      • et al.
      Oral glucose tolerance testing outcomes among women at high risk for gestational diabetes mellitus.
      20091460Single hospitalWHO15.344
       Nigeria
      • Anzaku A.S.
      • Musa J.
      Prevalence and associated risk factors for gestational diabetes in Jos, North-central, Nigeria.
      2011265Single hospitalWHO8.34
      Europe
       Belgium
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      20106727Single hospitalADA3.254
       France
      • Heude B.
      • Thiébaugeorges O.
      • Goua V.
      • Forhan A.
      • Kaminski M.
      • Foliguet B.
      • et al.
      Pre-pregnancy body mass index and weight gain during pregnancy: relations with gestational diabetes and hypertension, and birth outcomes.
      20121884Single hospitalADA4
       Hungary
      • Kun A.
      • Tornóczky J.
      • Tabák A.G.
      The prevalence and predictors of gestational diabetes mellitus in Hungary.
      20001835RegionalWHO8.665
       Ireland
      • Metzger B.E.
      • Gabbe S.G.
      • Persson B.
      • Buchanan T.A.
      • Catalano P.M.
      • et al.
      International Association of Diabetes & Pregnancy Study Groups (IADPSG) Consensus Panel Writing Group and the Hyperglycemia & Adverse Pregnancy Outcome (HAPO) Study Steering Committee
      The diagnosis of gestational diabetes mellitus: new paradigms or status quo?.
      20095500LocalWHO9.45
       Israel
      • Metzger B.E.
      • Gabbe S.G.
      • Persson B.
      • Buchanan T.A.
      • Catalano P.M.
      • et al.
      International Association of Diabetes & Pregnancy Study Groups (IADPSG) Consensus Panel Writing Group and the Hyperglycemia & Adverse Pregnancy Outcome (HAPO) Study Steering Committee
      The diagnosis of gestational diabetes mellitus: new paradigms or status quo?.
      20101818Single hospitalIADPSG10.064
       Israel
      • Metzger B.E.
      • Gabbe S.G.
      • Persson B.
      • Buchanan T.A.
      • Catalano P.M.
      • et al.
      International Association of Diabetes & Pregnancy Study Groups (IADPSG) Consensus Panel Writing Group and the Hyperglycemia & Adverse Pregnancy Outcome (HAPO) Study Steering Committee
      The diagnosis of gestational diabetes mellitus: new paradigms or status quo?.
      20101631Single hospitalIADPSG9.254
       Netherlands
      • Arendz I.J.
      • Oomen P.H.N.
      • Wolthuis A.
      • van der Velde N.M.
      • Kroese J.A.
      • van der Veen I.
      • et al.
      Prevalence of gestational diabetes in high-risk pregnancies: screened using an oral glucose tolerance test.
      2009471Single hospitalWHO24.24
       Norway
      • Jenum A.K.
      • Mørkrid K.
      • Sletner L.
      • Vangen S.
      • Vange S.
      • Torper J.L.
      • et al.
      Impact of ethnicity on gestational diabetes identified with the WHO and the modified International Association of Diabetes and Pregnancy Study Groups criteria: a population-based cohort study.
      2010759LocalIADPSG5
       Poland
      • Cypryk K.
      • Szymczak W.
      • Czupryniak L.
      • Sobczak M.
      • Lewiński A.
      Gestational diabetes mellitus – an analysis of risk factors.
      20062130Single hospitalWHO6.814
       Spain
      • Ramos-Leví A.M.
      • Pérez-Ferre N.
      • Fernández M.D.
      • Del Valle L.
      • Bordiu E.
      • Bedia A.R.
      • et al.
      Risk factors for gestational diabetes mellitus in a large population of women living in Spain: implications for preventative strategies.
      20101738Single hospitalIADPSG8.454
       Turkey
      • Karcaaltincaba D.
      • Kandemir O.
      • Yalvac S.
      • Güvendag-Guven S.
      • Haberal A.
      Prevalence of gestational diabetes mellitus and gestational impaired glucose tolerance in pregnant women evaluated by National Diabetes Data Group and Carpenter and Coustan criteria.
      200721534NationalNDDG3.177
       United Kingdom
      • Metzger B.E.
      • Gabbe S.G.
      • Persson B.
      • Buchanan T.A.
      • Catalano P.M.
      • et al.
      International Association of Diabetes & Pregnancy Study Groups (IADPSG) Consensus Panel Writing Group and the Hyperglycemia & Adverse Pregnancy Outcome (HAPO) Study Steering Committee
      The diagnosis of gestational diabetes mellitus: new paradigms or status quo?.
      20101671Single hospitalIADPSG17.054
       United Kingdom
      • Metzger B.E.
      • Gabbe S.G.
      • Persson B.
      • Buchanan T.A.
      • Catalano P.M.
      • et al.
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      20102376Single hospitalIADPSG24.284
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      2008924LocalADA7.45
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      20111608Single hospitalADA16.294
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      200810283LocalWHO12.545
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      19954998Multi-cityWHO4
       Cuba
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      • Martínez M.L.P.
      • Rodríguez Z.M.
      Clinical and epidemiological profile of diabetes mellitus in pregnancy, Isle of Youth, 2008.
      20111003RegionalWHO17.936
      South-East Asia
       Bangladesh
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      • Mahtab H.
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      Sociodemographic correlates of the increasing trend in prevalence of gestational diabetes mellitus in a large population of women between 1995 and 2005.
      2005950747RegionalADIPS3.776
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      Table 4Countries with data and countries grouped by data region for generation of the estimates of hyperglycaemia in pregnancy.
      Data regionCountries with selected data sourcesCountries extrapolated from data region
      AFRNigeriaAngola, Benin, Burkina Faso, Burundi, Botswana, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Djibouti, Democratic Republic of the Congo, Republic of Congo, Côte d’Ivoire, Eritrea, Ethiopia, Equatorial Guinea, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Liberia, Lesotho, Madagascar, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger, Rwanda, Réunion, Sao Tome and Principe, Senegal, Sierra Leone, Somalia, Seychelles, South Africa, Swaziland, United Republic of Tanzania, Togo, Uganda, Western Sahara, Zambia, Zimbabwe
      EUR-LMICPoland, TurkeyAlbania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Macedonia, Moldova, Montenegro, Romania, Russian Federation, Serbia, Tajikistan, Turkmenistan, Ukraine, Uzbekistan
      EUR-HICNorway, Ireland, Belgium, Spain, Hungary, France, Netherlands, United Kingdom, Israel, Sweden, ItalyAndorra, Austria, Channel Islands, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Germany, Greece, Iceland, Italy, Liechtenstein, Luxembourg, Malta, Monaco, Norway, Portugal, San Marino, Slovakia, Slovenia, Sweden, Switzerland, Faroe Islands
      MENA-LMICIslamic Republic of IranAfghanistan, Algeria, Egypt, Iraq, Jordan, Lebanon, Libya, Morocco, State of Palestine, Pakistan, Sudan, Syrian Arab Republic, Tunisia, Yemen, South Sudan
      MENA-HICQatar, United Arab EmiratesBahrain, Kuwait, Oman, Saudi Arabia
      NACUSA, Canada, Barbados, Trinidad and TobagoAnguilla, Antigua and Barbuda, Aruba, Bahamas, Belize, Bermuda, British Virgin Islands, Cayman Islands, Curaçao, Dominica, Grenada, Guadeloupe, Guyana, Haiti, Jamaica, Martinique, Mexico, Netherlands Antilles, Sint Maarten, St Lucia, St Kitts and Nevis, St Vincent and the Grenadines, Suriname, US Virgin Islands
      SACA-MICArgentina, Brazil, CubaBolivia, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, French Guiana, Guatemala, Honduras, Nicaragua, Panama, Paraguay, Peru, Uruguay, Venezuela
      SEA-LICBangladeshNepal
      SEA-MICIndia, Sri LankaBhutan, Maldives, Mauritius
      WP-LICViet NamCambodia, Democratic People's Republic of Korea, Lao People's Democratic Republic, Myanmar
      WP-MICChina, Thailand, MalaysiaFiji, Indonesia, Kiribati, Marshall Islands, Federated States of Micronesia, Mongolia, Nauru, Niue, Palau, Papua New Guinea, Philippines, Samoa, Solomon Islands, Timor L’Este, Tokelau, Tonga, Tuvalu, Vanuatu
      WP-HICAustralia, Japan, Singapore, Hong Kong SAR, Republic of KoreaBrunei Darussalam, Macau SAR Cook Islands, French Polynesia, Guam, New Caledonia, New Zealand, Taiwan
      AFR: Africa, EUR: Europe, MENA: Middle East and North Africa, NAC: North America and Caribbean, SACA: South and Central America, SEA: South-East Asia, WP: Western Pacific.
      HIC: high income countries, LIC: low income countries, LMIC: low and middle income countries, MIC; middle income countries.
      *Not enough information was available for some income-level groupings within geographic regions, therefore AFR-LIC was grouped with AFR-MIC, EUR-LIC was grouped with EUR-MIC, MENA-LIC was grouped with MENA-MIC, NAC-LIC and NAC-MIC were grouped with NAC-HIC.
      Eligible data sources were available from every IDF Region. More than half of the selected studies came from the IDF Europe (EUR) and North America and Caribbean (NAC) Region. The smallest number of identified studies came from the IDF Africa (AFR) Region. The majority of selected studies were conducted in high-income countries mainly in EUR and NAC. Almost half of all selected studies (20/46) were conducted in a single hospital, followed by studies conducted in a single city or area (12/46), 7 representing a region and 5 that were nationally representative.
      As different screening methods are available a huge variety can be seen in implementing these among different studies. The most common screening method applied among selected studies was a single step approach (31/46) such as that used by IADPSG, WHO 1999, ADIPS and EASD [
      American Diabetes Association: clinical practice recommendations 1999.
      ,
      • National Diabetes Data Group
      Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance.
      ,
      American Diabetes Association: clinical practice recommendations 2001.
      ,
      • Expert Committee on the Diagnosis and Classification of Diabetes Mellitus
      American Diabetes Association: clinical practice recommendations 2002.
      ,
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      ,
      • American Diabetes Association
      Clinical practice recommendations 2005.
      ,
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      ,
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      ,
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      ,
      • McElduff A.
      • Cheung N.W.
      • McIntyre H.D.
      • Lagström J.A.
      • Oats J.J.N.
      • Ross G.P.
      • et al.
      The Australasian Diabetes in Pregnancy Society consensus guidelines for the management of type 1 and type 2 diabetes in relation to pregnancy.
      ,
      • Canadian Diabetes Association Clinical Practice Guidelines Expert Committee
      Canadian Diabetes Association 2008 clinical practice guidelines for the prevention and management of diabetes in Canada.
      ,
      Diabetes mellitus. Report of a WHO Study Group.
      ,
      • Alberti K.G.
      • Zimmet P.Z.
      Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1. Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.
      ,
      • Metzger B.E.
      • Gabbe S.G.
      • Persson B.
      • Buchanan T.A.
      • Catalano P.M.
      • et al.
      International Association of Diabetes & Pregnancy Study Groups (IADPSG) Consensus Panel Writing Group and the Hyperglycemia & Adverse Pregnancy Outcome (HAPO) Study Steering Committee
      The diagnosis of gestational diabetes mellitus: new paradigms or status quo?.
      ]. Whereas studies in low- and lower-middle income countries most commonly used the WHO criteria (4/9), studies conducted in high- and upper-middle income countries most often used the IADPSG criteria (14/37). Studies using International Classification of Diseases (ICD)-classification were exclusively found in NAC high-income countries and predominantly in the United States.

      3. Discussion

      The methods presented in this paper are the first effort to create a comparable set of estimates of hyperglycaemia in pregnancy taking into account the great heterogeneity in methodology, representation, and study information available. Globally, screening methods and policy recommendation vary due to a previous lack of consensus on testing, diagnostic criteria, and screening methods [
      • Ferrara A.
      Increasing prevalence of gestational diabetes mellitus: a public health perspective.
      ]. The various existing screening methods which are currently in use were developed with the purpose of predicting onset of various perinatal and maternal complications. The variation in different approaches makes it difficult to directly compare reported prevalence rates from different studies even in the same country or region.
      A number of studies have looked at the effects on prevalence of using different diagnostic criteria on the same population [
      • Kalter-Leibovici O.
      • Freedman L.S.
      • Olmer L.
      • Liebermann N.
      • Heymann A.
      • Tal O.
      • et al.
      Screening and diagnosis of gestational diabetes mellitus: critical appraisal of the new International Association of Diabetes in Pregnancy Study Group recommendations on a national level.
      ,
      • Donovan L.
      • Hartling L.
      • Muise M.
      • Guthrie A.
      • Vandermeer B.
      • Dryden D.M.
      Screening tests for gestational diabetes: a systematic review for the U.S. Preventive Services Task Force.
      ,
      • Hollander M.H.
      • Paarlberg K.M.
      • Huisjes A.J.M.
      Gestational diabetes: a review of the current literature and guidelines.
      ,
      • Wendland E.M.
      • Torloni M.R.
      • Falavigna M.
      • Trujillo J.
      • Dode M.A.
      • Campos M.A.
      • et al.
      Gestational diabetes and pregnancy outcomes – a systematic review of the World Health Organization (WHO) and the International Association of Diabetes in Pregnancy Study Groups (IADPSG) diagnostic criteria.
      ,
      • Virally M.
      • Laloi-Michelin M.
      Methods for the screening and diagnosis of gestational diabetes mellitus between 24 and 28 weeks of pregnancy.
      ,
      • Schneider S.
      • Bock C.
      • Wetzel M.
      • Maul H.
      • Loerbroks A.
      The prevalence of gestational diabetes in advanced economies.
      ,
      • Agarwal M.M.
      • Dhatt G.S.
      • Shah S.M.
      Gestational diabetes mellitus: simplifying the international association of diabetes and pregnancy diagnostic algorithm using fasting plasma glucose.
      ,
      • Lapolla A.
      • Dalfrà M.G.
      • Ragazzi E.
      • De Cata A.P.
      • Fedele D.
      New International Association of the Diabetes and Pregnancy Study Groups (IADPSG) recommendations for diagnosing gestational diabetes compared with former criteria: a retrospective study on pregnancy outcome.
      ,
      • Moses R.G.
      • Morris G.J.
      • Petocz P.
      • San Gil F.
      • Garg D.
      The impact of potential new diagnostic criteria on the prevalence of gestational diabetes mellitus in Australia.
      ]. For the purpose of this methodology, the IADPSG criteria were taken as the reference criteria as they most closely match the new criteria proposed by the WHO. Therefore, other criteria were adjusted and studies comparing the IADPSG criteria to other methods were used to determine the necessary adjustments. Benhalima et al. compared prevalence of HFDP by using the IADPSG and the ADA criteria on the same population showing that the prevalence using IADPSG was effectively double what was found when applying ADA criteria [
      • Benhalima K.
      • Hanssens M.
      • Devlieger R.
      • Verhaeghe J.
      • Mathieu C.
      Analysis of pregnancy outcomes using the New IADPSG recommendation compared with the Carpenter and Coustan Criteria in an area with a low prevalence of gestational diabetes.
      ]. Similarly, Santos-Ayarzagoitia et al. (2006) compared prevalence in the same population by using NDDG, ADA and the WHO 1999 criteria. In that study, the prevalence of HFDP using the NDDG criteria was 3.2%, roughly a third of what was found when the 1999 WHO criteria were applied to the sample population (8.7%). The prevalence determined using the ADA criteria in this study was 4.1% [
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      ]. In addition, comparing the more closely related 1999 WHO criteria with the IADPSG criteria, O'Sullivan et al. found an increase in prevalence of more than 25% when IADPSG criteria was used compared with WHO 1999 criteria (IADPSG: 12.4%; WHO: 9.4%) [
      • O'Sullivan E.P.
      • Avalos G.
      • O’Reilly M.
      • Dennedy M.C.
      • Gaffney G.
      • Dunne F.
      Atlantic Diabetes in Pregnancy (DIP): the prevalence and outcomes of gestational diabetes mellitus using new diagnostic criteria.
      ]. These findings supported the assumptions applied in this methodology. However, more studies understanding the differences in criteria and their effect on the prevalence would strengthen the adjustments applied.
      In terms of representativeness, the vast majority of studies were conducted in single hospitals and therefore were of limited scope and subject to bias. National or regional population-based studies providing age-specific information for the prevalence of HIP would be ideal, although likely very resource intensive. Of the 19 nationally representative studies found, only five provided sufficient data to be included in the generation of estimates. The estimates and methodology would be greatly improved by the future application of a consistent method and criteria across studies and an effort to link data across large areas to improve representativeness.
      The new WHO definition is a step towards globally consistent screening and diagnostic methods, however it will take time for new guidelines to be recognised and implemented on a large scale. The approach taken here uses existing published information and adjusts prevalence data of various sources to generate estimates that are comparable and evidence-based. The reliability, accuracy and comparability of prevalence estimates of HIP are closely linked to the sources used to generate the estimates.

      4. Limitations

      The principal limitation in generating accurate estimates for HIP is the lack of high-quality data sources which are suitable for use. A number of studies were found to be lacking in information such as age-specific estimates or did not provide enough information in the description of the methods necessary to characterise the study. Where this information was lacking, every effort was made to contact investigators for more detail.
      Another major limitation is the lack of uniformity in the diagnostic criteria and screening methods used across various studies. This methodology is the first effort at standardising and making comparable estimates which take into account these differences, however, more information would be needed to improve precision.
      Data on fertility of women with diabetes is scarce. It was assumed that women with hyperglycaemia had the same fertility rates as the general population, as there was no evidence found in the literature indicating otherwise; nonetheless there could be a difference which has not been reported yet. There is a lack of research on the issue of fertility among the population with diabetes. One study was conducted on Swedish women with diagnosed type 1 diabetes prior to age 16 identified from the Swedish inpatient register from 1965–2004 [
      • Jonasson J.M.
      • Brismar K.
      • Sparén P.
      • Lambe M.
      • Nyrén O.
      • Östenson C.-G.
      • et al.
      Fertility in women with type 1 diabetes: a population-based cohort study in Sweden.
      ]. The study found women with type 1 diabetes had a standard fertility ratio of 0.8 compared with women without diabetes. However more data in different populations including women with T2DM is needed, therefore no adjustments were incorporated into these methods. A sensitivity analysis was performed to assess the impact of a lower fertility on the global estimates, results of the analysis are presented in the paper by Guariguata et al. [
      • Guariguata L.
      • Linnenkamp U.
      • Beagley J.
      • Whiting D.R.
      • Cho N.H.
      Global estimates of the prevalence of hyperglycaemia in pregnancy.
      ].
      Using fertility rates does not reflect the total pregnancies as fertility rates reflect the number of live birth. Some of the pregnancies not covered when using fertility rates may be affected by HIP even if they do not result in live births. The estimated global prevalence of HIP might therefore be an underestimate of total burden of HIP.
      The estimated proportion of HIP due to TDP are likely to be an underestimate as some women will be screened with hyperglycaemia severe enough to be classified as DIP but will not necessarily have had pre-existing undiagnosed T2DM. Additionally, the prevalence estimates of diabetes in women derived from the IDF Diabetes Atlas is taken from population-based studies that systematically exclude pregnant women. Thus, the true proportions of DIP and subsequently TDP in HIP are most likely higher.
      The selection process did not include whether or not risk based screening was done in a study. This might be a possible source of bias however of the 46 selected studies only 4 actually screened participants based on risk-factors.
      Included studies are mainly from high-income countries and estimates for countries that did not provide data have been aggregated from countries providing data to generate regional and global estimates. These country groupings are sensitive to regional and between country differences which we may not be aware of for a lack of data. For some regions only a limited number of studies were available and in particular for developing countries. As more data become available, the methodology may call for a more disaggregated matching and grouping of countries for extrapolation.

      5. Conclusion

      The new WHO guidelines for diagnosing HFDP should simplify future regional comparisons on the prevalence of HIP, as there now exists a classification system that has been internationally agreed [
      • Nolan C.J.
      Controversies in gestational diabetes.
      ]. However, implementation of the new criteria will take some time and uptake by various countries may not be consistent due to preference for regional criteria. Thus, a need to produce standard estimates which adjust for differences in criteria will likely be valuable for some time. Furthermore, a greater number of methodologically consistent studies on HIP are needed and especially in low- and middle-income countries.
      The methods used here to generate the estimated prevalence of HIP are simple, adaptable, and reproducible. The approach taken can be modified as new information is available. The estimates and methodology will be updated regularly to include new data and improve the precision of the estimate.

      Conflict of interest

      The authors have no conflicts of interest to disclose.

      Acknowledgements

      The authors wish to thank the IDF Diabetes Atlas Committee for reviewing and contributing to methodology described here. In addition, the authors wish to thank Prof. Boyd Metzger, Dr. David J. Pettitt, and Prof. Lois Jovanovič for independently reviewing the methodology. We also thank Dr. Lydia Makaroff for reading and commenting on the manuscript.
      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 .

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