title: Elevated HbA1c and fasting plasma glucose in predicting diabetes incidence among older adults: are two better than one?
abstract: OBJECTIVE
  To determine which measures-impaired fasting glucose (IFG), elevated HbA1c, or both-best predict incident diabetes in older adults.
  
  
  METHODS
  From the Health, Aging, and Body Composition study, we selected individuals without diabetes, and we defined IFG (100-125 mg/dL) and elevated HbA1c (5.7-6.4%) per American Diabetes Association guidelines. Incident diabetes was based on self-report, use of antihyperglycemic medicines, or HbA1c ≥6.5% during 7 years of follow-up. Logistic regression analyses were adjusted for age, sex, race, site, BMI, smoking, blood pressure, and physical activity. Discrimination and calibration were assessed for models with IFG and with both IFG and elevated HbA1c.
  
  
  RESULTS
  Among 1,690 adults (mean age 76.5, 46% men, 32% black), 183 (10.8%) developed diabetes over 7 years. Adjusted odds ratios of diabetes were 6.2 (95% CI 4.4-8.8) in those with IFG (versus those with fasting plasma glucose [FPG] <100 mg/dL) and 11.3 (7.8-16.4) in those with elevated HbA1c (versus those with HbA1c <5.7%). When FPG and HbA1c were considered together, odds ratios were 3.5 (1.9-6.3) in those with IFG only, 8.0 (4.8-13.2) in those with elevated HbA1c only, and 26.2 (16.3-42.1) in those with both IFG and elevated HbA1c (versus those with normal FPG and HbA1c). Addition of elevated HbA1c to the model with IFG resulted in improved discrimination and calibration.
  
  
  CONCLUSIONS
  Older adults with both IFG and elevated HbA1c have a substantially increased odds of developing diabetes over 7 years. Combined screening with FPG and HbA1c may identify older adults at very high risk for diabetes.
authors.affiliation: Corresponding author: Kasia J. Lipska, kasia.lipska@yale.edu.
authors.forename: Kasia J
authors.initials: KJ
authors.lastname: Lipska
authors.forename: Silvio E
authors.initials: SE
authors.lastname: Inzucchi
authors.forename: Peter H
authors.initials: PH
authors.lastname: Van Ness
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Gill
authors.forename: Alka
authors.initials: A
authors.lastname: Kanaya
authors.forename: Elsa S
authors.initials: ES
authors.lastname: Strotmeyer
authors.forename: Annemarie
authors.initials: A
authors.lastname: Koster
authors.forename: Karen C
authors.initials: KC
authors.lastname: Johnson
authors.forename: Bret H
authors.initials: BH
authors.lastname: Goodpaster
authors.forename: Tamara
authors.initials: T
authors.lastname: Harris
authors.forename: Nathalie
authors.initials: N
authors.lastname: De Rekeneire
mesh_terms: D000367:Age Factors; D000368:Aged; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism*; D001823:Body Composition; D003920:Diabetes Mellitus / Q000097:blood / Q000453:epidemiology*; D005215:Fasting / Q000097:blood*; D005260:Female; D005500:Follow-Up Studies; D005951:Glucose Tolerance Test; D006442:Glycated Hemoglobin / Q000378:metabolism*; D006801:Humans; D015994:Incidence; D008297:Male; D016017:Odds Ratio; D011236:Prediabetic State / Q000097:blood / Q000453:epidemiology; D011237:Predictive Value of Tests; D011379:Prognosis; D012189:Retrospective Studies; D012307:Risk Factors; D014481:United States / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin