Dataset Information

High Adiposity Is Associated With Higher Nocturnal and Diurnal Glycaemia, but Not With Glycemic Variability in Older Individuals Without Diabetes.

ABSTRACT: It is well known that adiposity is a risk factor for insulin resistance and type 2 diabetes mellitus. In the present study, we aimed to investigate the associations of measures of adiposity with indices of glycemia and of glycemic variability over a 72-h period in non-diabetic older adults.This cross-sectional study was conducted in non-diabetic individuals from the Active and Healthy Aging Study (N?=?228), Switchbox (N?=?116), and the Growing Old Together Study (N?=?94). Body mass index (BMI) and waist circumference were measured, and indices of glycemia and glycemic variability were derived from continuous glucose monitoring (CGM) using the Mini-Med® CGM system. Associations between adiposity and CGM were studied separately for the three cohorts, and derived estimates were subsequently meta-analyzed.After meta-analyzing the results from the separate cohorts, individuals with a higher BMI had higher levels of glycemia. Individuals with BMI between 30 and 35?kg/m2 had 0.28?mmol/L [95% confidence interval (CI): 0.12-0.44] higher 72?h-mean glucose concentration, 0.26?mmol/L (0.10-0.42) higher diurnal glucose (6:00 a.m. to 0:00 a.m.), and 0.39?mmol/L (0.19; 0.59) higher nocturnal glucose (3:00 a.m. to 6:00 a.m.) than participants with a normal weight (BMI 18.5-25?kg/m2). However, no associations were observed between higher BMI and glycemic variability. Results for glycemia and glycemic variability were similarly observed for a high waist circumference.High adiposity associates with constant higher mean glucose levels over the day in non-diabetic older adults.

SUBMITTER: Noordam R

PROVIDER: S-EPMC5960684 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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High Adiposity Is Associated With Higher Nocturnal and Diurnal Glycaemia, but Not With Glycemic Variability in Older Individuals Without Diabetes.

Noordam Raymond R Huurman Neline C NC Wijsman Carolien A CA Akintola Abimbola A AA Jansen Steffy W M SWM Stassen Stephanie S Beekman Marian M van de Rest Ondine O Slagboom P Eline PE Mooijaart Simon P SP van Heemst Diana D

Frontiers in endocrinology 20180514

<h4>Background</h4>It is well known that adiposity is a risk factor for insulin resistance and type 2 diabetes mellitus. In the present study, we aimed to investigate the associations of measures of adiposity with indices of glycemia and of glycemic variability over a 72-h period in non-diabetic older adults.<h4>Methods</h4>This cross-sectional study was conducted in non-diabetic individuals from the Active and Healthy Aging Study (<i>N</i> = 228), Switchbox (<i>N</i> = 116), and the Growing Old ...[more]

PMID: 29867770

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Project description:BACKGROUND/OBJECTIVE:There is substantial interest in dietary approaches to reducing postprandial glucose (PPG) responses, but the quantitative contribution of PPG to longer-term glycemic control (reflected in glycated hemoglobin, HbA1c) in the general population is not known. This study quantified the associations of preprandial glucose exposure, PPG exposure, and glycemic variability with HbA1c and estimated the explained variance in HbA1c in individuals with and without type 2 diabetes (T2D). SUBJECTS/METHODS:Participants in the A1c-Derived Average Glucose (ADAG) study without T2D (n = 77) or with non-insulin-treated T2D and HbA1c<6.5% (T2DHbA1c?<?6.5%, n = 63) or HbA1c???6.5% (T2DHbA1c???6.5%, n = 34) were included in this analysis. Indices of preprandial glucose, PPG, and glycemic variability were calculated from continuous glucose monitoring during four periods over 12 weeks prior to HbA1c measurement. In linear regression models, we estimated the associations of the glycemic exposures with HbA1c and calculated the proportion of variance in HbA1c explained by glycemic and non-glycemic factors (age, sex, body mass index, and ethnicity). RESULTS:The factors in the analysis explained 35% of the variance in HbA1c in non-diabetic individuals, 49% in T2DHbA1c?<?6.5%, and 78% in T2DHbA1c???6.5%. In non-diabetic individuals PPG exposure was associated with HbA1c in confounder-adjusted analyses (P?<?0.05). In the T2DHbA1c?<?6.5% group, all glycemic measures were associated with HbA1c (P?<?0.05); preprandial glucose and PPG accounted for 14 and 18%, respectively, of the explained variation. In T2DHbA1c???6.5%, these glycemic exposures accounted for more than 50% of the variation in HbA1c and with equal relative contributions. CONCLUSIONS:Among the glycemic exposures, PPG exposure was most strongly predictive of HbA1c in non-diabetic individuals, suggesting that interventions targeting lowering of the PPG response may be beneficial for long-term glycemic maintenance. In T2D, preprandial glucose and PPG exposure contributed equally to HbA1c.

Dataset Information

High Adiposity Is Associated With Higher Nocturnal and Diurnal Glycaemia, but Not With Glycemic Variability in Older Individuals Without Diabetes.

Publications

High Adiposity Is Associated With Higher Nocturnal and Diurnal Glycaemia, but Not With Glycemic Variability in Older Individuals Without Diabetes.

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