Prevalence of Gestational Diabetes Mellitus Detected by the National Diabetes Data Group or the Carpenter and Coustan Plasma Glucose Thresholds
- 1 September 2002
- journal article
- Published by American Diabetes Association in Diabetes Care
- Vol. 25 (9), 1625-1630
- https://doi.org/10.2337/diacare.25.9.1625
Abstract
OBJECTIVE—In 2000, the American Diabetes Association proposed the adoption of the Carpenter and Coustan criteria for diagnosis of gestational diabetes mellitus (GDM). The Carpenter and Coustan cutoffs are lower than the previously recommended National Diabetes Data Group (NDDG) values and would result in higher prevalence of GDM. Our aim is to estimate the magnitude of change in prevalence of GDM using the Carpenter and Coustan thresholds as compared with the NDDG thresholds by age and ethnicity. RESEARCH DESIGN AND METHODS—Cross-sectional study of 28,330 women aged 14–49 years who gave birth in 1996 and were members of the Northern California Kaiser Permanente Medical Care Program. Age, ethnicity, screening, and diagnostic test results were assessed from computerized hospitalization and laboratory systems. RESULTS—A total of 26,481 (94%) women were screened using a 50-g, 1-h oral glucose tolerance test, and 4,190 women underwent a diagnostic 100-g, 3-h oral glucose tolerance test after an abnormal screening. Overall, the GDM prevalence among screened women was 3.2% (95% CI 3.0–3.4) by NDDG and 4.8% (95% CI 4.5–5.1) by Carpenter and Coustan criteria, and based on either threshold, it increased with age (P < 0.001). The age-adjusted GDM prevalence by NDDG and Carpenter and Coustan criteria, respectively, was 5.0 and 7.4% in Asians, 3.9 and 5.6% in Hispanics, 3.0 and 4.0% in African-Americans, and 2.4 and 3.8% in whites. Proportional increments were larger in women aged <25 years (70%) and in whites (58%). CONCLUSIONS—The prevalence of GDM increased, on average, by 50% with use of the Carpenter and Coustan thresholds. Relative increments were greater in low-risk age and ethnic groups. This information would be useful for clinical settings in predicting cost of GDM based on demographic characteristics of the population.Keywords
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