the study was conducted within the framework of the bruneck study , a long - term , prospective population - based survey of atherosclerosis and its risk factors carried out in bruneck ( northeastern italy ) , with a baseline evaluation in 1990 ( 5 ) . among 1,000 randomly sampled caucasian men and women aged 4079 years , 936 volunteered . after excluding the few individuals with incomplete data , those with diabetes at baseline , and the very few lost to follow - up , in the remaining 842 subjects new cases of type 2 diabetes were registered in the follow - up examinations of 1995 , 2000 , and 2005 . information about medical history , drug use , and lifestyle was collected by a questionnaire . weight , height , waist and hip circumferences , and blood pressure were measured with standard techniques . at the baseline and follow - up examinations , venous blood was sampled in the morning after an overnight fast for laboratory measurements , including fasting plasma glucose ( fpg ) and hba1c ( diabetes control and complications trial  aligned assay ; equipment and reagents from biorad , milan , italy , at both baseline and follow - up examinations ) . at both baseline and follow - up , diabetes was diagnosed when hba1c was 6.5% or diabetes treatment was ongoing . in a parallel analysis , diabetes was diagnosed when fpg was 7.0 mmol / l or diabetes treatment was ongoing . subjects were stratified into four hba1c categories ( < 5.0 , 5.005.49 [ reference ] , 5.505.99 , and 6.006.49% ) . the hba1c category 5.005.49% had the largest number of participants ( n = 345 ) and was used as the reference . hazard ratios ( hrs ) for type 2 diabetes in the hba1c categories were estimated with cox proportional hazards models . model 2 also included ldl and hdl cholesterol , log - transformed triglycerides , bmi , waist - to - hip ratio , hypertension , family history of diabetes , education , alcohol , physical activity , and smoking . model 3 included the variables in model 2 plus variables that are abnormal in conditions potentially affecting hba1c ( white blood cell count , hemoglobin , ferritin , and creatinine ) . additional models were run with updated variables ( hba1c and other variables were assessed every 5 years during follow - up ) . in these models , baseline hba1c predicted diabetes in the first 5-year follow - up period , hba1c at the 5-year follow - up predicted diabetes in the following 5-year follow - up , and so forth in multivariable equations overcoming the limitations of single measures . in parallel analyses , the same models were run with impaired fasting glucose ( ifg ) as a risk variable , and diabetes was diagnosed with fpg at baseline and follow - up . all information about medical history , drug use , and lifestyle was collected by a questionnaire . weight , height , waist and hip circumferences , and blood pressure were measured with standard techniques . at the baseline and follow - up examinations , venous blood was sampled in the morning after an overnight fast for laboratory measurements , including fasting plasma glucose ( fpg ) and hba1c ( diabetes control and complications trial  aligned assay ; equipment and reagents from biorad , milan , italy , at both baseline and follow - up examinations ) . at both baseline and follow - up , diabetes was diagnosed when hba1c was 6.5% or diabetes treatment was ongoing . in a parallel analysis , diabetes was diagnosed when fpg was 7.0 mmol / l or diabetes treatment was ongoing . subjects were stratified into four hba1c categories ( < 5.0 , 5.005.49 [ reference ] , 5.505.99 , and 6.006.49% ) . the hba1c category 5.005.49% had the largest number of participants ( n = 345 ) and was used as the reference . hazard ratios ( hrs ) for type 2 diabetes in the hba1c categories were estimated with cox proportional hazards models . model 2 also included ldl and hdl cholesterol , log - transformed triglycerides , bmi , waist - to - hip ratio , hypertension , family history of diabetes , education , alcohol , physical activity , and smoking . model 3 included the variables in model 2 plus variables that are abnormal in conditions potentially affecting hba1c ( white blood cell count , hemoglobin , ferritin , and creatinine ) . additional models were run with updated variables ( hba1c and other variables were assessed every 5 years during follow - up ) . in these models , baseline hba1c predicted diabetes in the first 5-year follow - up period , hba1c at the 5-year follow - up predicted diabetes in the following 5-year follow - up , and so forth in multivariable equations overcoming the limitations of single measures . in parallel analyses , the same models were run with impaired fasting glucose ( ifg ) as a risk variable , and diabetes was diagnosed with fpg at baseline and follow - up . all the table shows that incident cases of type 2 diabetes increased across categories of hba1c : approximately one of four subjects from the 6.006.49% category ( high normal ) developed diabetes over 15 years . in this category , type 2 diabetes risk was 13- to 16-fold increased ( models 0 and 1 ) . the risk was only slightly reduced after adjusting for several putative confounding factors ( models 2 and 3 ) and was definitely greater when updated variables were included into the models ( table 1 ) . analyses including interaction terms between hba1c categories and factors that might affect interpretation of hba1c ( i.e. , white blood cell count , hemoglobin , ferritin , and creatinine ) did not yield evidence of differential associations according to hba1c level , supporting the lack of effect modification . hrs for 15-year incidence of type 2 diabetes according to hba1c model 0 was unadjusted . model 2 included the variables in model 1 plus ldl and hdl cholesterol levels , log - transformed triglyceride levels , bmi , waist - to - hip ratio , hypertension , family history of diabetes , education , alcohol use , physical activity score , and smoking status . model 3 included all variables in model 2 plus white blood cell count , hemoglobin , ferritin , and creatinine . * cox models in which hba1c and other variables at baseline were used to predict diabetes in the 15-year follow - up . cox models in which updated hba1c and other variables were used to predict diabetes in subsequent 5-year follow - up periods ( see text for details ) . in parallel analyses in which diabetes was diagnosed at both baseline and follow - up with fpg , and in which subjects at risk were those in the ifg category , we found that the latter conferred an increased diabetes risk ( hrs [ 95% cis ] in subjects with ifg vs. normal fpg [ < 5.55 mmol / l ] : 8.20 [ 4.6614.40 ] , 7.72 [ 4.3613.66 ] , 5.83 [ 3.2310.54 ] , and 5.92 [ 3.2410.80 ] in the four models , respectively ) . however , diabetes risk in subjects with ifg was substantially lower than in subjects with high - normal hba1c . it is well known that hba1c captures chronic hyperglycemia in the prior 23 months , is well correlated to chronic diabetes complications , and has less preanalytical problems and biological variability than plasma glucose , with a noninferior standardization ( 7 ) . for such reasons , the findings of the current study confirm a progressively increased risk of type 2 diabetes across categories of hba1c and clearly document that subjects with high - normal hba1c have a strong risk of developing type 2 diabetes , even after adjusting for several putative risk factors ( e.g. , bmi ) and potentially confounding variables ( e.g. , anemia ) . remarkably , diabetes risk in subjects with high - normal hba1c is higher than in subjects with ifg . noteworthy , our study population was entirely caucasian , and subjects were aged > 40 years . therefore , our findings can not be necessarily extrapolated to other ethnicities and/or to younger subjects . to the best of our knowledge , this study is the first to examine how baseline hba1c predicts hba1c - diagnosed diabetes . our findings , which are consistent with those of studies based on self - reported diagnosis of diabetes ( 3,4 ) , more strongly support the ada recommendations of using hba1c for diabetes risk stratification and including subjects with high - normal levels in an effective prevention strategy . these subjects , indeed , have a high rate of progression to diabetes and deserve particular attention in order to prevent or delay the disease . specific intervention trials , however , are needed to confirm such a conclusion because those conducted so far , based on lifestyle changes and/or drug use , recruited subjects at risk according to their plasma glucose levels and not hba1c .
objectiveglycosylated hemoglobin ( hba1c ) recently has been recommended for the diagnosis of diabetes by the american diabetes association , but its value in the prediction of type 2 diabetes is poorly understood . in this study 
 we evaluated how high - normal hba1c levels predict type 2 diabetes.research design and methodswe measured hba1c in 919 caucasian subjects , aged 4079 years , and recorded new cases of type 2 diabetes in the following 15 years . 
 diabetes was diagnosed with hba1c.resultssubjects were stratified according to baseline hba1c ( < 5.0 , 5.005.49 [ reference ] , 5.505.99 , and 6.006.49% ) . 
 sex- and age - adjusted hazard ratios ( 95% ci ) for type 2 diabetes were 1.11 ( 0.304.41 ) , 1.00 , 3.79 ( 1.798.06 ) , and 12.50 ( 5.5128.34 ) , respectively . 
 results did not change after adjusting for several putative confounding factors and were confirmed when models with updated variables were used.conclusionshba1c is an independent risk factor for type 2 diabetes . 
 subjects with high - normal levels of hba1c deserve particular attention because they have a strong risk of developing diabetes .