Glucose-independent, black-white differences in hemoglobin A1c levels: a cross-sectional analysis of 2 studies

David C Ziemer, Paul Kolm, William S Weintraub, Viola Vaccarino, Mary K Rhee, Jennifer G Twombly, K M Venkat Narayan, David D Koch, Lawrence S Phillips
Annals of Internal Medicine 2010 June 15, 152 (12): 770-7

BACKGROUND: A previous study of participants with prediabetes found that hemoglobin A(1c) (HbA(1c)) levels differed between black and white participants with no differences in glucose concentration.

OBJECTIVE: To determine whether black-white differences in HbA(1c) level are present in other populations and across the full spectrum of glycemia.

DESIGN: Cross-sectional, retrospective.

SETTING: Outpatient.

PARTICIPANTS: 1581 non-Hispanic black and white participants between 18 and 87 years of age without known diabetes in the SIGT (Screening for Impaired Glucose Tolerance) study and 1967 non-Hispanic black and white participants older than 40 years without known diabetes in the NHANES III (Third National Health and Nutrition Examination Survey).

MEASUREMENTS: HbA(1c) levels, anthropometry, and plasma glucose levels during oral glucose tolerance testing.

RESULTS: Hemoglobin A(1c) levels were higher in black than in white participants with normal glucose tolerance (0.13 percentage point [P < 0.001] in the SIGT sample and 0.21 percentage point [P < 0.001] in the NHANES III sample), prediabetes (0.26 percentage point [P < 0.001] and 0.30 percentage point [P < 0.001], respectively), or diabetes (0.47 percentage point [P < 0.020] and 0.47 percentage point [P < 0.013], respectively) after adjustment for plasma glucose levels and other characteristics known to correlate with HbA(1c) levels.

LIMITATION: The mechanism for the differences is unknown.

CONCLUSION: Black persons have higher HbA(1c) levels than white persons across the full spectrum of glycemia, and the differences increase as glucose intolerance worsens. These findings could limit the use of HbA(1c) to screen for glucose intolerance, indicate the risk for complications, measure quality of care, and evaluate disparities in health.

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