Dataset Information

Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study.

ABSTRACT:

Objective

Various methods are used to quantify postprandial glycemia or glucose variability, but few have been compared and none are standardized. Our objective was to examine the relationship among common indexes of postprandial glycemia, overall hyperglycemia, glucose variability, and A1C using detailed glucose measures obtained during everyday life and to study which blood glucose values of the day provide the strongest prediction of A1C.

Research design and methods

In the A1C-Derived Average Glucose (ADAG) study, glucose levels were monitored in 507 participants (268 type 1 diabetic, 159 type 2 diabetic, and 80 nondiabetic subjects) with continuous glucose monitoring (CGM) and frequent self-monitoring of blood glucose (SMBG) during 16 weeks. We calculated several indexes of glycemia and analyzed their intercorrelations. The association between glucose measurements at different times of the day (pre- and postprandial) and A1C was examined using multiple linear regression.

Results

Indexes of glucose variability showed strong intercorrelation. Among postprandial indexes, the area under the glucose curve calculated from CGM 2 h after a meal correlated well with the 90-min SMBG postprandial measurements. Fasting blood glucose (FBG) levels were only moderately correlated with indexes of hyperglycemia and average or postprandial glucose levels. Indexes derived with SMBG strongly correlated with those from CGM. Some SMBG time points had a stronger association with A1C than others. Overall, preprandial glucose values had a stronger association with A1C than postprandial values for both diabetes types, particularly for type 2 diabetes.

Conclusions

Indexes of glucose variability and average and postprandial glycemia intercorrelate strongly within each category. Variability indexes are weakly correlated with the other categories, indicating that these measures convey different information. FBG is not a clear indicator of general glycemia. Preprandial glucose values have a larger impact on A1C levels than postprandial values.

SUBMITTER: Borg R

PROVIDER: S-EPMC2889756 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study.

Borg Rikke R Kuenen Judith C JC Carstensen Bendix B Zheng Hui H Nathan David M DM Heine Robert J RJ Nerup Jorn J Borch-Johnsen Knut K Witte Daniel R DR

Diabetes 20100427 7

<h4>Objective</h4>Various methods are used to quantify postprandial glycemia or glucose variability, but few have been compared and none are standardized. Our objective was to examine the relationship among common indexes of postprandial glycemia, overall hyperglycemia, glucose variability, and A1C using detailed glucose measures obtained during everyday life and to study which blood glucose values of the day provide the strongest prediction of A1C.<h4>Research design and methods</h4>In the A1C- ...[more]

PMID: 20424232

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Project description:BackgroundElucidating associations between exposures to ambient air pollutants and profiles of cognitive performance may provide insight into neurotoxic effects on the aging brain.ObjectiveWe examined associations between empirically derived profiles of cognitive performance and residential concentrations of particulate matter of aerodynamic diameter < 2.5 (PM2.5) and nitrogen dioxide (NO2) in older women.MethodWomen (N = 2,142) from the Women's Health Initiative Study of Cognitive Aging completed a neuropsychological assessment measuring attention, visuospatial, language, and episodic memory abilities. Average yearly concentrations of PM2.5 and NO2 were estimated at the participant's addresses for the 3 years prior to the assessment. Latent profile structural equation models identified subgroups of women exhibiting similar profiles across tests. Multinomial regressions examined associations between exposures and latent profile classification, controlling for covariates.ResultFive latent profiles were identified: low performance across multiple domains (poor multi-domain; n = 282;13%), relatively poor verbal episodic memory (poor memory; n = 216; 10%), average performance across all domains (average multi-domain; n = 974; 45%), superior memory (n = 381; 18%), and superior attention (n = 332; 15%). Using women with average cognitive ability as the referent, higher PM2.5 (per interquartile range [IQR] = 3.64μg/m3) was associated with greater odds of being classified in the poor memory (OR = 1.29; 95% Confidence Interval [CI] = 1.10-1.52) or superior attention (OR = 1.30; 95% CI = 1.10-1.53) profiles. NO2 (per IQR = 9.86 ppb) was associated with higher odds of being classified in the poor memory (OR = 1.38; 95% CI = 1.17-1.63) and lower odds of being classified with superior memory (OR = 0.81; 95% CI = 0.67-0.97).ConclusionExposure to PM2.5 and NO2 are associated with patterns of cognitive performance characterized by worse verbal episodic memory relative to performance in other domains.

Dataset Information

Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study.

Objective

Research design and methods

Results

Conclusions

Publications

Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study.

Similar Datasets

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