Glucose variability in subjects with normal glucose tolerance: Relations with body composition, insulin secretion and sensitivity

• Published in: Diabetes & metabolic syndrome clinical research & reviews Vol. 16; no. 1; p. 102387
• Main Authors: Klimontov, Vadim V., Semenova, Julia F.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.01.2022
• Subjects: Blood Glucose; Blood Glucose Self-Monitoring; Body Composition; Continuous glucose monitoring; Glucose; Glucose variability; Humans; Insulin; Insulin Resistance; Insulin Secretion; Middle Aged; Continuous glucose monitoring; Glucose variability; Insulin resistance; Body composition; Insulin secretion
• ISSN: 1871-4021; 1878-0334
• DOI: 10.1016/j.dsx.2022.102387

To estimate the determinants of glucose variability (GV) in young and middle-aged non-obese subjects with normal glucose tolerance (NGT) we assessed relations between GV parameters, body composition, insulin secretion and sensitivity indices. Thirty individuals with normal body mass index (BMI) and twenty overweight subjects were included. 24-hour mean glucose, time in range, time above range (TAR), time below range (TBR), standard deviation (SD), coefficient of variation (CV), mean amplitude of glucose excursions (MAGE), continuous overlapping net glycemic action (CONGA), J-index, lability index (LI), mean absolute glucose (MAG), M-value, high blood glucose index (HBGI), low blood glucose index (LBGI) were derived from continuous glucose monitoring. Body composition was assessed by DEXA. Insulin secretion and sensitivity was estimated by HOMA-IR and HOMA-B scores. Overweight subjects demonstrated higher mean glucose, CONGA, J-index and lower TBR, M-value and LBGI values. Mean glucose correlated positively with total, trunk, gynoid and android fat mass, while M-value and LBGI demonstrated negative correlations with these parameters. In multiple stepwise regression analysis, android fat mass was a predictor of mean glucose, CONGA, J-index, SD and MAGE, gynoid fat mass predicted J-index only, and total fat mass was associated inversely with MAG. Fasting insulin was a predictor of TAR, SD, CV, MAGE, MAG, LI and HBGI. HOMA-B was associated with CONGA, M-value and LBGI. In non-obese subjects with NGT mean glucose and GV parameters are related to fat mass and fat distribution. These relations can be mediated through insulin secretion and sensitivity. ∙Overweight subjects with normal glucose tolerance have higher mean monitored glucose then those with normal body weight.∙Abdominal fat mass and fasting insulin determine glucose variability in non-obese non-diabetic subjects.