Joshua R Sparks1, Mark A Sarzynski2, J Mark Davis2, Peter W Grandjean3, Xuewen Wang2. 1. Reproductive Endocrinology and Women's Health Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA. 2. Department of Exercise Science, Noman J. Arnold School of Public Health, University of South Carolina, Columbia, SC. 3. Department of Health, Exercise Science, and Recreation Management, School of Applied Sciences, University of Mississippi, Oxford, MS.
Abstract
Introduction/Purpose: Overweight or obese adults spend more time sedentary and less time performing physical activity (PA) and are at an increased risk for developing impaired glycemic health. Free-living environments may provide insight into glycemic health in addition to clinical assessments. The purpose of this study was to examine the relationship between PA and glycemic health assessed by continuous glucose monitoring (CGM). Methods: Twenty-eight overweight or obese adults each wore an accelerometer and CGM over the same 7 consecutive days. Average daily time (minutes and metabolic-equivalent minutes (MET-minutes)) and associated energy expenditure performing light (LPA), moderate-to-vigorous (MVPA), total PA, and standard deviation (SD) across days were calculated. Average daily 24-h and waking glycemia, mean glucose concentration, glycemic variability measured as the continuous overlapping net glycemic action, mean amplitude of glycemic excursions, and mean of daily difference were assessed. Results: LPA MET-minutes per day was positively associated with 24-h and waking glycemia time-in-range and negatively associated with 24-h and waking time in hyperglycemia. Total PA time and the SD of MVPA and total PA time were negatively associated with 24-h mean glucose concentration. Individual-level analysis identified that most participants (50%-71%) expressed negative associations between LPA and MVPA time with 24-h mean glucose concentration, mean amplitude of glycemic excursion, and 4-h continuous overlapping net glycemic action. Conclusions: Expectedly, greater total PA time and intensity-specific PA time were associated with lower 24-h and waking mean glucose concentration, greater glycemia time-in-range, and less time in hyperglycemia. The relationship between glucose concentrations and PA time SD was unexpected, whereas most participants expressed hypothesized relationships, which necessitates further exploration.
Introduction/Purpose: Overweight or obese adults spend more time sedentary and less time performing physical activity (PA) and are at an increased risk for developing impaired glycemic health. Free-living environments may provide insight into glycemic health in addition to clinical assessments. The purpose of this study was to examine the relationship between PA and glycemic health assessed by continuous glucose monitoring (CGM). Methods: Twenty-eight overweight or obese adults each wore an accelerometer and CGM over the same 7 consecutive days. Average daily time (minutes and metabolic-equivalent minutes (MET-minutes)) and associated energy expenditure performing light (LPA), moderate-to-vigorous (MVPA), total PA, and standard deviation (SD) across days were calculated. Average daily 24-h and waking glycemia, mean glucose concentration, glycemic variability measured as the continuous overlapping net glycemic action, mean amplitude of glycemic excursions, and mean of daily difference were assessed. Results: LPA MET-minutes per day was positively associated with 24-h and waking glycemia time-in-range and negatively associated with 24-h and waking time in hyperglycemia. Total PA time and the SD of MVPA and total PA time were negatively associated with 24-h mean glucose concentration. Individual-level analysis identified that most participants (50%-71%) expressed negative associations between LPA and MVPA time with 24-h mean glucose concentration, mean amplitude of glycemic excursion, and 4-h continuous overlapping net glycemic action. Conclusions: Expectedly, greater total PA time and intensity-specific PA time were associated with lower 24-h and waking mean glucose concentration, greater glycemia time-in-range, and less time in hyperglycemia. The relationship between glucose concentrations and PA time SD was unexpected, whereas most participants expressed hypothesized relationships, which necessitates further exploration.
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