TY - JOUR
T1 - Effects of diabetes definition on global surveillance of diabetes prevalence and diagnosis: A pooled analysis of 96 populationbased studies with 331 288 participants
AU - Panza, Francesco
AU - Danaei, Goodarz
AU - Fahimi, Saman
AU - Lu, Yuan
AU - Zhou, Bin
AU - Hajifathalian, Kaveh
AU - Di Cesare, Mariachiara
AU - Lo, Wei-Cheng
AU - Reis-Santos, Barbara
AU - Cowan, Melanie J
AU - Shaw, Jonathan Edward
AU - Bentham, James
AU - Lin, John Kent
AU - Bixby, Honor
AU - Magliano, Dianna Josephine
AU - Bovet, Pascal
AU - Miranda, J Jaime
AU - Khang, Young-Ho
AU - Stevens, Gretchen A
AU - Riley, Leanne A
AU - Ali, Mohammed K
AU - Ezzati, Majid
AU - Abdeen, Ziad A
AU - Abdul Kadir, Khalid
AU - Abu-Rmeileh, Niveen Me E
AU - Acosta-Cazares, Benjamin
AU - Aguilar-Salinas, Carlos A
AU - Ahmadvand, Alireza
AU - Nsour, Mohannad Al
AU - Alkerwi, Ala a
AU - Amouyel, Philippe
AU - Andersen, Lars Bo
AU - Anderssen, Sigmund A
AU - Andrade, Dolores S
AU - Anjana, Ranjit Mohan
AU - Aounallah-Skhiri, Hajer
AU - Aris, Tahir
AU - Arlappa, Nimmathota
AU - Arveiler, Dominique
AU - Assah, Felix K
AU - Avdicova, Maria
AU - Balakrishna, Nagalla
AU - Bandosz, Piotr
AU - Barbagallo, Carlo M
AU - Barcelo, Alberto
AU - Batieha, Anwar M
AU - Baur, Louise A
AU - Romdhane, Habiba Ben
AU - Bernabe-Ortiz, Antonio
AU - Bhargava, Santosh K
AU - Bi, Yufang
PY - 2015
Y1 - 2015
N2 - Background: Diabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2h 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 populationbased health examination surveys in different regions. Methods: We used data from 96 populationbased 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 FPGor2hOGTT 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 randomeffects model. We assessed the sources of heterogeneity of sensitivity by metaregressions for study characteristics selected a priori. Findings: Population prevalence of diabetes based on FPGor2hOGTT was correlated with prevalence based on FPG alone (r=0?98), but was higher by 26 percentage points at different prevalence levels. Prevalence based on HbA1c was lower than prevalence based on FPG in 42?8 of agesexsurvey 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 glucosebased and HbA1cbased 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?354 ?3 ) and a pooled specificity of 99?74 (99?7199 ?78 ) compared with FPG 7?0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes
defined based on FPGor2hOGTT was 30?5 (28?732 ?3 ). None of the preselected studylevel 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 HbA1cbased definition alone in health surveys will not identify a substantial proportion of previously undiagnosed people who would be considered as having diabetes using a glucosebased test.
AB - Background: Diabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2h 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 populationbased health examination surveys in different regions. Methods: We used data from 96 populationbased 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 FPGor2hOGTT 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 randomeffects model. We assessed the sources of heterogeneity of sensitivity by metaregressions for study characteristics selected a priori. Findings: Population prevalence of diabetes based on FPGor2hOGTT was correlated with prevalence based on FPG alone (r=0?98), but was higher by 26 percentage points at different prevalence levels. Prevalence based on HbA1c was lower than prevalence based on FPG in 42?8 of agesexsurvey 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 glucosebased and HbA1cbased 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?354 ?3 ) and a pooled specificity of 99?74 (99?7199 ?78 ) compared with FPG 7?0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes
defined based on FPGor2hOGTT was 30?5 (28?732 ?3 ). None of the preselected studylevel 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 HbA1cbased definition alone in health surveys will not identify a substantial proportion of previously undiagnosed people who would be considered as having diabetes using a glucosebased test.
U2 - 10.1016/S22138587
DO - 10.1016/S22138587
M3 - Article
VL - 3
SP - 624
EP - 637
JO - The Lancet Diabetes and Endocrinology
JF - The Lancet Diabetes and Endocrinology
SN - 2213-8587
IS - 8
ER -