Effects of school-based high-intensity interval training on body composition, cardiorespiratory fitness and cardiometabolic markers in adolescent boys with obesity: a randomized controlled trial.

With accumulating evidence suggesting that CVD has its origins in childhood obesity. The purpose of this study was to determine the effect of a real-world school-based high-intensity interval training intervention on body composition, cardiorespiratory fitness and cardiometabolic markers in obese boys aged 10 to 13 years. Forty-five adolescent boys with obesity (age = 11.2 ± 0.7 years, BMI = 24.2 ± 1.0 kg/m2), were randomized to high-intensity interval training group (HIIT, n = 15), moderate-intensity continuous training group (MICT, n = 15), or a control group (CON, n = 15). The intervention groups performed three weekly exercise sessions over 12 weeks. HIIT group performed two sets of eight bouts of 15 s run at high-intensity [90 ~ 100% maximal aerobic speed (MAS)] separated by eight bouts of 15 s recovery run at low-intensity (50% MAS), MICT group performed 30 min run at moderate intensity (60 ~ 70% MAS) and CON group were instructed to continue their normal behaviors. All participants had indices of body composition, cardiorespiratory fitness (CRF) and cardiometabolic markers measured at baseline and post-intervention. Statistical differences between and within groups were determined by use of two-way analysis of variance (ANOVA) with repeated measures. Following the school-based training program, BMI and body fat mass decreased (BMI: - 1.8 kg/m2 vs. - 1.2 kg/m2, P < 0.01; FM: - 1.6 kg, P < 0.05 vs. -3.7 kg, P < 0.01) in HIIT and MICT group, but there was no significant difference between the two interventions; [Formula: see text] both increased significantly in two intervention groups, and the increment of HIIT group was significantly greater than that of MICT (6.1 mL/kg/min vs. 3.8 mL/kg/min, P < 0.01), Visceral adipose tissue was significant decrease in HIIT group (- 53 g vs. -17 g, P < 0.01) whilst the MICT group experienced a significant decrease in body fat percentage (- 3.1 ± 1.0 kg, P < 0.01), but there were no significant difference between the two interventions. Low-density lipoprotein cholesterol decreased only in HIIT group (- 17.2%, P < 0.05). Significant decrease in the usual index of insulin resistance (HOMA-IR) occurred in HIIT and MICT groups (- 27.3 and - 28.6%, respectively; P < 0.05). Our results demonstrated that high-intensity interval training based on running can be used to improve the physical health of obese adolescents in school. Further investigations involving a larger cohort of participants, taken from different schools, is recommended. title Effect of High Intensity Interval Training on Obese Children and Adolescents, time 16/12/2017, ID ChiCTR-IOR-17013992 , website http://www.chictr.org.cn.

Meng C ，Yucheng T ，Shu L ，Yu Z ... -  《BMC Pediatrics》

Effect of High-Intensity Interval Training on Fitness, Fat Mass and Cardiometabolic Biomarkers in Children with Obesity: A Randomised Controlled Trial.

Dias KA ，Ingul CB ，Tjønna AE ，Keating SE ，Gomersall SR ，Follestad T ，Hosseini MS ，Hollekim-Strand SM ，Ro TB ，Haram M ，Huuse EM ，Davies PSW ，Cain PA ，Leong GM ，Coombes JS ... -  《-》

HIIT is superior than MICT on cardiometabolic health during training and detraining.

Gripp F ，Nava RC ，Cassilhas RC ，Esteves EA ，Magalhães COD ，Dias-Peixoto MF ，de Castro Magalhães F ，Amorim FT ... -  《-》

Low-Frequency HIIT Improves Body Composition and Aerobic Capacity in Overweight Men.

Chin EC ，Yu AP ，Lai CW ，Fong DY ，Chan DK ，Wong SH ，Sun F ，Ngai HH ，Yung PSH ，Siu PM ... -  《-》

A Comparative Study of Health Efficacy Indicators in Subjects with T2DM Applying Power Cycling to 12 Weeks of Low-Volume High-Intensity Interval Training and Moderate-Intensity Continuous Training.

This study is aimed at comparing the effects of different exercise intensities, namely, high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT), on body composition, heart and lung fitness, and blood glucose, and blood pressure indices in patients with type 2 diabetes mellitus (T2DM), using power cycling. A total of 96 T2DM volunteers who met the inclusion criteria were recruited from a hospital in Yangpu, Shanghai. Based on the blood index data of their medical examination results which comprised blood pressure, fasting blood glucose, hemoglobin A1c (HbA1c), and insulin, 37 volunteers were included in the study. Exercise prescription was determined based on T2DM exercise guidelines combined with medical diagnosis and exercise test results, and the patients were randomly assigned to three groups: HIIT group, MICT group, and control (CON) group. HIIT involved one-minute power cycling (80%-95% maximal oxygen uptake (VO2max)), one-minute passive or active rest (25%-30% VO2max), and two-minute rounds of eight groups. MICT required the use of a power bike for 30 minutes of continuous training (50%-70% VO2max) five times a week. The CON group was introduced to relevant medicine, exercise, and nutrition knowledge. The exercise interventions were completed under the supervision of an exercise instructor and hospital doctors. The same indicators were measured after 12 weeks of intervention, and the results of the two tests within and between groups were analyzed for comparison. The weight index of the MICT intervention showed statistically significant within-group differences (difference = 3.52, 95% CI = 2.11-4.92, p = 0.001 < 0.01); group differences for the MICT and CON groups were also statistically significant (difference = 3.52 ± 2.09, Cd1 = -0.39 ± 1.25, p = 0.004 < 0.01). Body mass index (BMI) analysis revealed that the overall means of BMI indicators were not statistically different between groups (F = 0.369, p = 0.694 > 0.05) and the before and after values of the MICT and CON (difference = -1.30 ± 0.79, Cd1 = -0.18 ± 0.45, p = 0.001 < 0.01). No statistically significant difference was observed in the overall mean VO2max index between the groups after the 12-week intervention (F = 2.51, p = 0.100 > 0.05). A statistically significant difference was found in the overall means of the data between the two groups (difference = 0.32, 95% CI = 0.23-0.40, p = 0.001 < 0.01). Analysis of fasting blood glucose (FBG) indicators revealed statistically significant differences between the MICT and control groups (p = 0.028 < 0.05). Analysis of HbA1c and fasting insulin (FI) indicators revealed no statistically significant difference in the overall HbA1c index after the 12-week exercise intervention (F = 0.523, p = 0.598 > 0.05), and the overall difference before and after the experiment between the groups was statistically significant (F = 6.13, p = 0.006 < 0.01). No statistically significant difference was found in the FI index overall after the 12-week exercise intervention (F = 2.50, p = 0.1 > 0.05). Analysis of systolic blood pressure (SBP) revealed statistically significant difference before and after the HIIT and CON interventions (Hd7 = -1.10 ± 1.79, Cd7 = 1.2 ± 1.31, p = 0.018 < 0.05) and statistically significant difference before and after the MICT and CON interventions (Md7 = -0.99 ± 0.91, Cd7 = 1.40 ± 1.78, p = 0.02 < 0.05). The diastolic blood pressure (DBP) revealed no statistically significant within-group differences before and after. Exercise interventions applying both low-volume HIIT and MICT, with both intensity exercises designed for power cycling, improved health-related indicators in the participants; low-volume HIIT had more time advantage. The current experiment compared HIIT with MICT in a safe manner: 50% of the exercise time produced similar benefits and advantages in the two indicators of VO2max and FI. However, MICT was superior to HIIT in the two indicators of body weight (weight) and BMI. The effect of power cycling on FI has the advantages of both aerobic and resistance exercise, which may optimize the type, intensity, and time of exercise prescription according to the individual or the type of exercise program. Our results provide a reference for the personalization of exercise prescription for patients with T2DM.

Li J ，Cheng W ，Ma H 《-》