| Title | Effects of diabetes definition on global surveillance of diabetes prevalence and diagnosis: a pooled analysis of 96 population-based studies with 331288 participants |
| Authors | Danaei, Goodarz Fahimi, Saman Lu, Yuan Zhou, Bin Hajifathalian, Kaveh Di Cesare, Mariachiara Lo, Wei-Cheng Reis-Santos, Barbara Cowan, Melanie J. Shaw, Jonathan E. Bentham, James Lin, John K. Bixby, Honor Magliano, Dianna Bovet, Pascal Miranda, J. Jaime Khang, Young-Ho Stevens, Gretchen A. Riley, Leanne M. Ali, Mohammed K. Ezzati, Majid Abdeen, Ziad A. Kadir, Khalid Abdul Abu-Rmeileh, Niveen M. Acosta-Cazares, Benjamin Aekplakorn, Wichai Aguilar-Salinas, Carlos A. Ahmadvand, Alireza Al Nsour, Mohannad Alker |
| Affiliation | Harvard TH Chan Sch Publ Hlth, Boston, MA USA. Univ London Imperial Coll Sci Technol & Med, London W2 1PG, England. Natl Taiwan Univ, Taipei, Taiwan. Univ Fed Pelotas, Capao Do Leao, RS, Brazil. World Hlth Org, Geneva, Switzerland. Baker IDI Heart & Diabet Inst, Melbourne, Vic, Australia. Univ San Francisco, San Francisco, CA 94117 USA. Univ Lausanne, CH-1015 Lausanne, Switzerland. Minist Hlth, Victoria, Seychelles. Univ Peruana Cayetano Heredia, San Martin De Porres, Peru. Seoul Natl Univ, Seoul 151, South Korea. Emory Univ, Atlanta, GA 30322 USA. Al Quds Univ, Jerusalem, Israel. Monash Univ Malaysia, Subang Jaya, Selangor, Malaysia. Birzeit Univ, Jerusalem, Israel. Inst Mexicano Seguro Social, Mexico City, DF, Mexico. Mahidol Univ, Bangkok 10700, Thailand. Inst Nacl Ciencias Med & Nutr Salvador Zubiran, Mexico City, DF, Mexico. Univ Tehran Med Sci, Tehran, Iran. Eastern Mediterranean Publ Hlth Network, Amman, Jordan. Luxembourg Hlth Inst, Luxembourg, Luxembourg. 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Kailuan Gen Hosp, Tangshan, Hebei, Peoples R China. Minist Agr, Inst Food & Nutr Dev, Beijing, Peoples R China. Chinese Ctr Dis Control & Prevent, Beijing, Peoples R China. Univ Padua, I-35100 Padua, Italy. Ctr Diabet & Endocrine Care, Bangalore, Karnataka, India. Med Univ Gdansk, Gdansk, Poland. Chinese Ctr Dis Control & Prevent, Beijing, Peoples R China. |
| Keywords | FASTING PLASMA-GLUCOSE HEMOGLOBIN A(1C) MEASUREMENT GLYCATED HEMOGLOBIN CARDIOVASCULAR-DISEASE WORLDWIDE STANDARDIZATION CONSENSUS STATEMENT SYSTEMATIC ANALYSIS INSULIN-RESISTANCE SCREENING-TEST TOLERANCE TEST |
| Issue Date | 2015 |
| Publisher | LANCET DIABETES & ENDOCRINOLOGY |
| Citation | LANCET DIABETES & ENDOCRINOLOGY.2015,3,(8),624-637. |
| Abstract | 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 HbA(1c). 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 HbA(1c) (HbA(1c) >= 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 HbA(1c) 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 HbA(1c)-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 HbA(1c) 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 HbA(1c) 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 HbA(1c)-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. |
| URI | http://hdl.handle.net/20.500.11897/417748 |
| ISSN | 2213-8587 |
| DOI | 10.1016/S2213-8587(15)00129-1 |
| Indexed | SCI(E) |
| Appears in Collections: | 待认领 |
