Saudi Cultural Missions Theses & Dissertations
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Item Restricted Effects of Physical Activity, Exercise and Breakfast Timing Manipulations on Glucose Metabolism in Healthy Adolescents(Saudi Digital Library, 2025-10-27) Afeef, Sahar; Tolfrey, Keith; Barrett, Laura A; Zakrzewski-Fruer, Julia KPostprandial hyperglycaemia is associated with an increased risk of type 2 diabetes (T2D) and cardiovascular disease (CVD). Even in healthy individuals, hyperglycaemia can adversely impact cardiometabolic health. Multiple rises and falls in glucose concentrations (i.e., glycaemic variability) may harm vascular health. Since most of the day is often spent in a postprandial state, measuring glucose concentrations over this critical period is vital to assess glycaemic profile. The novelty of continuous glucose monitoring (CGM) systems enables the assessment of glycaemic variability and postprandial glycaemia with reduced invasiveness and under free-living conditions. Since cardiometabolic risk factors were found to begin early in life, interventions focusing on moderating postprandial glycaemia and glycaemic variability through physical activity (PA) and diet manipulations should start early in life. Therefore, this thesis aimed to investigate postprandial glycaemic responses and glycaemic variability in relation to PA, exercise and breakfast timing manipulations in healthy adolescents aged 11 to 14 years. The first experimental study, Chapter 4, compared interstitial fluid glucose concentration ([ISFG]) obtained by CGM (i.e., FreeStyle Libre) against capillary plasma glucose concentration ([CPG], reference method) in response to an oral glucose tolerance test (OGTT, 5 time points including fasting) and treadmill exercise at different intensities (5 time points) in 17 healthy adolescents (9 girls, mean ± SD age 12.8 ± 0.9 y, BMI 18.4 ± 2.1 kg∙m−2). The overall mean absolute relative difference was 13.1 ± 8.5%. The [ISFG] was significantly lower than [CPG] 15 (−1.16 mmol·L−1, −9.7%) and 30 min (−0.74 mmol·L−1, −4.6%) after OGTT. Yet, post-OGTT glycaemic responses assessed by total (tAUC) and incremental (iAUC) area under the curves were not significantly different with trivial to small effect sizes (P ≥ 0.084, d = 0.14 – 0.45). These results indicate that CGM is an acceptable device reflecting postprandial glycaemic responses (i.e., AUC) that have high relevance to CVD risk. Non-significant site by timepoint interactions were observed during the treadmill exercise tests (P ≥ 0.614), indicating that the pattern of [ISFG] assessed by CGM was similar to [CPG] across the time points. Consequently, CGM were used in the two subsequent studies (Chapters 5 & 6). Using objective monitoring devices (i.e., Actigraph and CGM), Chapter 5 examined the associations of daily glycaemic variability with sedentary time and PA levels measured under free-living conditions in 37 healthy adolescents (24 girls, 12.7 ± 1.0 y, 20.1 ± 3.7 kg∙m−2). Glycaemic variability measures were not significantly associated with time spent sedentary and PA levels after accounting for age, sex, maturity status, accelerometer wear time and % body fat (P ≥ 0.071). However, there are some potential associations between glycaemic variability measures and sedentary time and MVPA. The findings suggest that accumulating 60 min MVPA daily tended to associate with 0.04 mmol∙L−1 reduction in StDevG (β = –0.00068, P = 0.087) and 0.7% reduction in glucose CV (β = –0.012038, P = 0.086). The magnitude of changes is small, and the metabolic health implications of such reductions are not known. Furthermore, the results suggest that accumulating 60 min of sedentary time seems to be associated with 0.3% higher glucose CV (β = 0.005692, P = 0.071), yet the same duration spent in MVPA tends to be associated with 0.7% lower glucose CV (β = –0.012038, P = 0.086), suggesting a greater impact of MVPA on glycaemic variability. Thus, encouraging reduced sedentary time combined with participation in MVPA may reduce glycaemic variability in healthy adolescents with small variations in blood glucose concentrations. Using CGM, Chapter 6 investigated the acute effect of school-based exercise bouts on postprandial glycaemia and 24 h glycaemic variability in 14 healthy adolescents (6 girls, 12.8 ± 1.0 y, 18.0 ± 1.6 kg∙m−2). The participants performed three experimental conditions in a fixed pre-determined order on three consecutive days: day 1) moderate intensity exercise condition (MIE, 30-min continuous brisk walking); day 2) no-exercise control condition (CON); day 3) high intensity intermittent exercise condition (HIIE, 30-min of 10 × 30-s sprints interspersed with 2.5-min brisk walking bouts). They performed the exercise conditions or no-exercise then consumed three standardised meals (breakfast and lunch at school and dinner at home) at fixed times. Thirty-minute bouts of MIE and HIIE did not change postprandial glycaemia (P ≥ 0.203) or 24-h glycaemic variability (P ≥ 0.281) significantly in this small sample of healthy adolescents. Although non-significant, the reduction in post-breakfast glucose iAUC was moderate for MIE (−0.24 mmol·L−1; P = 0.589; d = 0.77) and large for HIIE (−0.26 mmol·L−1; P = 0.444; d = 0.86) compared with CON. Non-significant, moderate (0.37 mmol·L−1; P = 0.219; d = 0.70) and large (0.42 mmol·L−1; P = 0.203; d = 0.81) increases in post-lunch glucose iAUC were observed for MIE and HIIE compared with CON. Furthermore, the effect size in post-dinner glucose iAUC were trivial to small between conditions, suggesting a short residual effect of exercise lasting for two meals. The mismatch between the probability values and effect sizes was a consequence of the COVID-reduced sample. The ramifications of these exercise effects are unclear and need to be confirmed in a larger sample of adolescents. The last experimental study, Chapter 7, examined the effect of early morning (EM-BC, 08:30) and mid-morning (MM-BC, 10:30) breakfast consumption compared with breakfast omission (BO) on the glycaemic and insulinaemic responses to the second meal (i.e., lunch) in 15 healthy adolescent girls (13.1 ± 0.8 y, 19.8 ± 3.1 kg∙m−2) who skipped breakfast habitually. The main finding from this study was that MM-BC significantly reduced post-lunch glucose tAUC (–10%; P = 0.002, d = 0.68) and iAUC (–36%; P < 0.001, d = 1.44) compared with BO, with moderate to large effects. However, the EM-BC resulted in non-significant reductions in post-lunch glucose tAUC (–5%; P = 0.195, d = 0.36) and iAUC (–15%; P = 0.077, d = 0.52) compared with BO, with small to moderate effects. Furthermore, MM-BC resulted in moderate reductions in post-lunch peak glucose compared with both BO (–1.03 mmol·L−1; P = 0.001, d = 0.74) and EM-BC (–1.03 mmol·L−1; P = 0.001, d = 0.74), with no significant difference between EM-BC and BO (P = 1.00, d = 0.001). Lastly, MM-BC resulted in a moderate, significant reduction in glycaemic variability across the 6 h experimental period compared with BO (–4.4%; P = 0.008, d = 0.56) yet the difference was trivial between EM-BC and BO (–1.1%; P = 1.00, d = 0.14). Although a second-meal effect was not found after EM-BC, the results of this study are important because they demonstrate that the timing of breakfast or the interval between the 1st and 2nd meals may be important for breakfast skipping girls. In summary, the information presented in this thesis extends the knowledge on glycaemic variability in relation to daily PA, exercise bouts and breakfast timing interventions in healthy adolescents. This thesis demonstrates an acceptable performance of FreeStyle Libre and the practicality of using this tool under free-living conditions with adolescents. This thesis provides further evidence of the potential benefit of engaging in daily MVPA and reducing sedentary time to lower glycaemic variability. In addition, thirty-minute bouts of MIE and HIIE reduced postprandial glycaemic response to a breakfast meal consumed in close proximity to exercise, but not to lunch or dinner, suggesting a short-term effect of exercise on glycaemia. Finally, consuming breakfast in the mid-morning (e.g., during the school break) may promote the metabolic health of girls who habitually skip breakfast by moderating the post-lunch glycaemic response.8 0