In a Free-Living Setting, Obesity Is Associated With Greater Food Intake in Response to a Similar Premeal Glucose Nadir

Abstract

Purpose Changes in blood glucose levels have been shown to influence eating in healthy individuals; however, less is known about effects of glucose on food intake in individuals who are obese (OB). The goal of this study was to determine the predictive effect of circulating glucose levels on eating in free-living OB and normal weight (NW) individuals. Methods Interstitial glucose levels, measured with a continuous glucose monitor (CGM) system, were obtained from 15 OB and 16 NW volunteers (age: 40 ± 14 and 37 ± 12 years; weight: 91 ± 13 and 68 ± 12 kg; hemoglobin A1c: 5.1% ± 0.7% and 5.2% ± 0.4%, respectively). While wearing the CGM, participants filled out a food log (mealtime, hunger rating, and amount of food). Glucose profiles were measured in relation to their meals [macro program (CGM peak and nadir analysis) using Microsoft® Excel]. Results OB and NW individuals showed comparable CGM glucose levels: mean [OB = 100 ± 8 mg/dL; NW = 99 ± 13 mg/dL; P = nonsignificant (NS)] and SD (OB = 18 ± 5 mg/dL, NW = 18 ± 4 mg/dL; P = NS). Obesity was associated with slower postprandial rate of changing glucose levels (P = 0.04). Preprandial nadir glucose levels predicted hunger and food intake in both groups (P < 0.0001), although hunger was associated with greater food intake in OB individuals than in NW individuals (P = 0.008 for group interaction). Conclusions Premeal glucose nadir predicted hunger and food intake in a group of free-living, healthy, nondiabetic NW and OB individuals; however for a similar low glucose level stimulus, hunger-induced food intake was greater in OB than NW individuals.

Analytical Performance of the Factory-Calibrated Flash Glucose Monitoring System FreeStyle Libre2TM in Healthy Women

“…Along with clinical applications, CGM systems are also widely used for research [6][7][8][9][10] to provide comprehensive glycaemic profiles, including glucose nadir [7], glucose peak [9] and area under the curve [10]. These devices are often utilised in studies under freeliving conditions, as they remove the barrier of collecting blood samples in the laboratory.…”

Subclinical Reactive Hypoglycemia with Low Glucose Effectiveness—Why We Cannot Stop Snacking despite Gaining Weight

“…However, studies using CGM in people without diabetes have been scarce, and glucose variability in seemingly healthy people has not been fully studied. Recently, Kim et al examined the CGM of healthy nondiabetic individuals in a free-living setting and found that glucose nadirs before a meal predicted subsequent hunger and food intake [ 21 ]. In addition, using CGM in their prospective cohorts, Wyatt et al showed that the average postprandial glucose dips 2–3 h after a standardized meal (890 kcal, 86 g of carbohydrates, 53 g of fat, 16 g of protein, and 2 g of fiber, ingested within 10 min) relative to baseline level are significantly associated with an increase in hunger postprandial for 2–3 h, a shorter time until the next meal, and greater postprandial energy intake [ 22 ].…”

Deficits in brain glucose transport among younger adults with obesity

“…A growing body of work has suggested that obesity is associated with changes in central sensing and utilization of glucose [5][6][7]. Functional magnetic resonance imaging (MRI) studies have shown that the regional blood-oxygen-level-dependent (BOLD) signal, which is often used as a surrogate measure for brain activity, is different in individuals with obesity, particularly when peripheral blood glucose levels are controlled using hyperglycemic and hypoglycemic clamp studies [6,7].…”