James M. Hempe

Introduction: People with a low or high haemoglobin glycation index (HGI) have lower or higher HbA1c than other people with the same FPG. This study compared the prevalence of prediabetes based on FPG, 2hOGTT and HbA1c in people with low, moderate or high HGI.Methods: Prediabetes was diagnosed based on ADA cutpoints in 10,488 NHANES participants without self‐reported diabetes. HGI was calculated as the difference between a participant's observed HbA1c and a predicted HbA1c where predicted HbA1c = 0.024 FPG + 3.1. Participants were divided into low (HGI < −0.15%), moderate (HGI −0.15% to +0.15%) and high (HGI > +0.15%) HGI subgroups.Results: The prevalence of prediabetes was 42.4% based on FPG, 27.2% based on HbA1c and 17.2% based on 2hOGTT. FPG and HbA1c thus overdiagnosed prediabetes by 25.2% and 10.0%, respectively, compared to the OGTT gold standard. Prevalence was (1) similar in low, moderate and high HGI participants based on 2hOGTT, (2) highest in low HGI participants based on FPG, and (3) highest in high HGI participants based on HbA1c. Among participants with mismatched FPG and HbA1c, OGTT was normal in (1) 79.5% of participants with normal FPG but prediabetic HbA1c (mean HGI = +0.53%), and (2) 75.2% of participants with normal HbA1c but prediabetic FPG (mean HGI = −0.30%).Conclusions: FPG overdiagnosed prediabetes in people with low HGI. HbA1c overdiagnosed prediabetes in people with high HGI. Clinical use of HGI could improve prediabetes diagnosis and help health care providers avoid inappropriate or delayed treatment of people with extremes of HGI.

We examined the relationship between two malleable risk factors, depressive symptoms and fear of hypoglycemia, in children and adolescents with Type 1 diabetes and their relationship to two important outcomes, adherence behaviors and metabolic control. To assess this relationship, we used a multidimensional measure of adherence, assessing frequency of both blood glucose monitoring and healthy behaviors including diet and exercise. We predicted that higher levels of depressive symptoms and higher levels of fear of hypoglycemia would be associated with worse metabolic control as mediated by poor adherence. Eighty-three children and adolescents ages 8 to 20 (M = 13.87, SD 3.21) were recruited from March 2014 to October 2014 at an outpatient diabetes clinic in a moderately sized Southeastern city within the USA. Nested models were evaluated using structural equation modeling. Adherence significantly mediated the relationship between depressive symptoms and metabolic control with more depressive symptoms leading to worse metabolic control. Adherence marginally mediated the relationship between fear of hypoglycemia and metabolic control; however, less fear of hypoglycemia was associated with worse metabolic control. In a combined model, adherence continued to significantly mediate the relationship between depressive symptoms and metabolic control, while also independently significantly mediating the relationship between fear of hypoglycemia and metabolic control. This finding was also contrary to the predicted relationship with less fear of hypoglycemia leading to worse metabolic control. The results indicate that youth with fewer depressive symptoms and more fear of hypoglycemia had better adherence to their treatment regimen, which was associated with better metabolic control. The results of this study highlight the importance of screening for depression and fear of hypoglycemia during routine clinic visits to optimize adherence and metabolic control.

Objective: Fasting plasma glucose (FPG), 2-hour plasma glucose (2hPG) from a 75-g oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) can lead to different results when diagnosing prediabetes and diabetes. The Hemoglobin Glycation Index (HGI) quantifies the interindividual variation in glycation resulting in discrepancies between FPG and HbA1c. We used data from the Vitamin D and Type 2 Diabetes (D2d) study to calculate HGI, to identify HGI-associated variables, and to determine how HGI affects prediabetes and diabetes diagnosis. Measurements: A linear regression equation [HbA1c (%) = 0.0164 × FPG (mg/dL) + 4.2] was derived using the screening cohort (n = 6829) and applied to calculate predicted HbA1c. This was subtracted from the observed HbA1c to determine HGI in the baseline cohort with 2hPG data (n = 3945). Baseline variables plus prediabetes and diabetes diagnosis by FPG, HbA1c, and 2hPG were compared among low, moderate, and high HGI subgroups. Results: The proportion of women and Black/African American individuals increased from low to high HGI subgroups. Mean FPG decreased and mean HbA1c increased from low to high HGI subgroups, consistent with the HGI calculation; however, mean 2hPG was not significantly different among HGI subgroups. Conclusions: High HGI was associated with Black race and female sex as reported previously. The observation that 2hPG was not different across HGI subgroups suggests that variation in postprandial glucose is not a significant source of population variation in HGI. Exclusive use of HbA1c for diagnosis will classify more Black individuals and women as having prediabetes compared with using FPG or 2hPG.

Background Racial variation in the relationship between blood glucose and hemoglobin A1c (HbA1c) complicates diabetes diagnosis and management in racially mixed populations. Understanding why HbA1c is persistently higher in blacks than whites could help reduce racial disparity in diabetes outcomes. Objective Test the hypothesis that neighborhood disadvantage is associated with inflammation and poor metabolic control in a racially mixed population of pediatric type 1 diabetes patients. Methods Patients (n = 86, 53 white, 33 black) were recruited from diabetes clinics. Self‐monitored mean blood glucose (MBG) was downloaded from patient glucose meters. Blood was collected for analysis of HbA1c and C‐reactive protein (CRP). Patient addresses and census data were used to calculate a concentrated disadvantage index (CDI). High CDI reflects characteristics of disadvantaged neighborhoods. Results HbA1c and MBG were higher (p < 0.0001) in blacks [10.4% (90.3 mmol/mol), 255 mg/dL] than whites [8.9% (73.9 mmol/mol), 198 mg/dL). CDI was higher in blacks (p < 0.0001) and positively correlated with HbA1c (r = 0.40, p = 0.0002) and MBG (r = 0.35, p = 0.0011) unless controlled for race. CDI was positively associated with CRP by linear regression within racial groups. CRP was not different between racial groups, and was not correlated with MBG, but was positively correlated with HbA1c when controlled for race (p = 0.04). Conclusions Neighborhood disadvantage was associated with inflammation and poor metabolic control in pediatric type 1 diabetes patients. Marked racial differences in potential confounding factors precluded differentiation between genetic and environmental effects. Future studies should recruit patients matched for neighborhood characteristics and treatment regimen to more comprehensively assess racial variation in HbA1c.

Drs. Riddle and Gerstein (1) suggest renaming the hemoglobin glycation index (HGI) to reflect the possibility that interindividual variation in HGI in the ACCORD trial could be an artifact of how blood glucose was measured. HGI is the difference between an individual’s observed HbA1c and a predicted HbA1c derived by inserting a time-matched blood glucose measurement into a regression equation describing the linear population relationship between blood glucose and HbA1c. In our analysis of ACCORD (2), we used baseline HbA1c and fasting plasma glucose (FPG) to show that high HGI at baseline (i.e., HbA1c higher than predicted by FPG) was …

Context: Inflammation is associated with higher glycated hemoglobin (HbA1c) levels. Whether the relationship is independent of blood glucose concentration remains unclear. Objective: The hemoglobin glycation index (HGI) was used to test the hypothesis that interindividual variation in HbA1c is associated with inflammation. Participants: This study used nondiabetic adults from the National Health and Nutrition Examination Survey (1999–2008). Main Outcome Measures: A subsample of participants was used to estimate the linear regression relationship between HbA1c and fasting plasma glucose (FPG). Predicted HbA1c were calculated for 7323 nondiabetic participants by inserting FPG into the equation, HbA1c = 0.017× FPG (mg/dL) + 3.7. HGI was calculated as the difference between the observed and predicted HbA1c and the population was divided into low, moderate, and high HGI subgroups. Polymorphonuclear leukocytes (PMNL), monocytes, and C-reactive protein (CRP) were used as biomarkers of inflammation. Results: Mean HbA1c, CRP, monocyte, and PMNL levels, but not FPG, progressively increased in the low, moderate, and high HGI subgroups. There were disproportionately more Blacks than whites in the high HGI subgroup. CRP (ß, 0.009; 95% confidence interval [CI], 0.0001–0.017), PMNL (ß, 0.036; 95% CI, 0.010–0.062), and monocyte count (ß, 0.072; 95% CI, 0.041–0.104) were each independent predictors of HGI after adjustment for age, sex, race, triglycerides, hemoglobin level, mean corpuscular volume, red cell distribution width, and obesity status. Conclusions: HGI reflects the effects of inflammation on HbA1c in a nondiabetic population of U.S. adults and may be a marker of risk associated with inflammation independent of FPG, race, and obesity.

OBJECTIVE: This study tested the hypothesis that intensive treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial disproportionately produced adverse outcomes in patients with diabetes with a high hemoglobin glycation index (HGI = observed HbA1c − predicted HbA1c). RESEARCH DESIGN AND METHODS: ACCORD was a randomized controlled trial of 10,251 patients with type 2 diabetes assigned to standard or intensive treatment with HbA1c goals of 7.0% to 7.9% (53 to 63 mmol/mol) and less than 6% (42 mmol/mol), respectively. In this ancillary study, a linear regression equation (HbA1c = 0.009 × fasting plasma glucose [FPG] [mg/dL] + 6.8) was derived from 1,000 randomly extracted participants at baseline. Baseline FPG values were used to calculate predicted HbA1c and HGI for the remaining 9,125 participants. Kaplan-Meier and Cox regression were used to assess the effects of intensive treatment on outcomes in patients with a low, moderate, or high HGI. RESULTS: Intensive treatment was associated with improved primary outcomes (composite of cardiovascular events) in the low (hazard ratio [HR] 0.75 [95% CI 0.59–0.95]) and moderate (HR 0.77 [95% CI 0.61–0.97]) HGI subgroups but not in the high HGI subgroup (HR 1.14 [95% CI 0.93–1.40]). Higher total mortality in intensively treated patients was confined to the high HGI subgroup (HR 1.41 [95% CI 1.10–1.80]). A high HGI was associated with a greater risk for hypoglycemia in the standard and intensive treatment groups. CONCLUSIONS: HGI calculated at baseline identified subpopulations in ACCORD with harms or benefits from intensive glycemic control. HbA1c is not a one-size-fits-all indicator of blood glucose control, and taking this into account when making management decisions could improve diabetes care.