OR26-05 The Correction Factor for A1C in Anemic Patients

Abstract Diabetes can be defined by hemoglobinA1c (A1c), fasting plasma glucose (FPG), and 2-hour plasma glucose (2hPG). Despite that A1c has a tendency for underestimation of the prevalence of diabetes and overestimation of the prevalence of normal glucose tolerance, A1c is the most convenient method, since no preparation required. However, various factors could affect A1c. The objective of this project is to identify the covariates that affect A1c. The study sample included 9,952 adults (age≥20 years old) from the 2005–2016 NHANES. Subjects with established diabetes were excluded, and we analyzed subject’s documented BMI, A1c, FPG, 2hPG, Hemoglobin (Hgb), race/ethnicity, age, education, poverty index, family history of diabetes, and tobacco and alcohol consumption to determine their impact on A1C measurement. Continuous data were expressed as means with standard deviation. Either t-test or ANOVA was used to examine the influence of covariates on continuous variables. We examined the relation of A1c with FPG, 2hPG, and other covariates. With backward regression analysis, we excluded the covariates without significant impact on A1c. All the analyses were conducted in SYSTAT 13, Systat Software, Inc. In the univariate analysis, A1c was significantly corelated with FPG (r=0.5692, P<0.0001) and 2hPG (r=0.5122, P<0.0001). In the backward regression analysis, education, poverty index, and family history of diabetes were excluded for their low impact on A1c. In addition to FPG and 2hPG, gender (r=-0.0527, P<0.0001), age (r=0.1746, P<0.0001), BMI (r=0.0978, P<0.0001), race/ethnicity (r=0.0478, P< 0.0001), current alcohol consumption (r=0.0542, P<0.0001), current smoker (r=-0.0806, P<0.0001), and Hgb (r=-0.1526, P<0.0001) had significant impact on A1c. Due to the significant difference in Hgb between gender, gender-based analyses were performed. In male gender, the impact of other covariates (age, BMI, race/ethnicity, current alcohol consumption, and current smoker) than FPG and 2hPG could be explained at least partially through their impact on Hgb (P<0.0001). Each 1 g/dL decrease of Hgb would falsely decrease A1c by 0.053% (P<0.0001). In female gender, the impact of covariates other than FPG and 2hPG on A1c could be explained by their impact on Hgb (p<0.0001) except for BMI. Each 1 g/dL decrease of Hgb would falsely decrease A1c by 0.047% (P<0.0001). In addition to FPG and 2hPG, A1c could be affected by gender, age, BMI, race/ethnicity, current alcohol consumption, and current smoker through their impact on Hgb, except for BMI in female gender. A1c will be falsely decreased by 0.053% in male gender and 0.047% in female gender for each 1 g/dL decrement of Hgb. Thus, A1c should be interpreted with caution in anemic patients. We propose using the gender specific correction factors for more accurate interpretation of A1c.