Increased resting blood pressure (BP) is a risk factor for many health complications. The prevalence of elevated BP is growing among adolescents. There is a need to investigate effective ways of decreasing excessive blood pressure in this age group. The study aim was to determine the effect of 10-weeks High-Intensive Interval Training (HIIT)—Tabata protocol—introduced in physical education (PE) lessons on resting blood pressure in adolescents. The sample included 52 boys aged 16.23 ± 0.33 years body height176.74 ± 6.07 (m), body weight 65.42 ± 12.51 (kg), BMI 20.89 ± 3.53 (kg/m2) and 89 girls aged 16.12 ± 0.42 years, body height 164.38 ± 6.54 (m), body weight 56.71 ± 10.23 (kg), BMI 20.93 ± 3.08 (kg/m2) from secondary school. Based on resting BP, the fractions of boys and girls with normal BP and high BP were identified and divided into experimental (EG) and control (CG) groups. EG completed a 10-weeks HIIT program (three cycles of Tabata protocol) implemented in one PE lesson during a week. The duration of the effort was 14 min. The intensity was at 75–80% of maximal heart rate. Changes in systolic and diastolic BP after the experiment were examined. The results indicated the improvement in SBP in EG with high BP compared to the rest of the groups (average reduction of 12.77 mmHg; p < 0.0001). The EG normotensive had a statistically significant higher reduction of SBP comparing CG normotensive (average decrease of 1.81 mmHG; p = 0.0089). HIIT effectively decreases BP in adolescents. Implementing HIIT in PE lessons in secondary school is recommended to improve BP parameters.

Analysis of the interventions on cardiovascular disease risk factors focuses on quantitative changes, omitting assessment of positive effect frequency in individuals. The aim of this study was to assess the prevalence of positive effects of high-intensity interval training (HIIT) on body composition, cardiovascular parameters, and cardiorespiratory fitness among adolescents. A total of 52 boys and 89 girls from a secondary school were separated into an experimental group (EG) with HIIT and a control group (CG). Body fat % (BFP), resting systolic blood pressure (SBP), diastolic blood pressure (DBP), and fitness index (FI) changes were calculated. We assessed the influence and interaction of three factors: intervention (INT), sex (SEX), and body mass index (BMIstatus) on the ratio of individuals with and without positive changes. We used log-linear models for interactions and multivariate correspondence analysis (MCA). The results indicate that HIIT affects the prevalence of positive changes in SBP, DBP, and FI. Interactions between factors suggest boys with low BMI get more benefit from the intervention than girls. The MCA indicates a relationship between FI and BFP and between BP parameters. The effectiveness of HIIT was confirmed concerning the prevalence of the positive changes in measured parameters. We suggest that HIIT should be implemented in PE lessons, although there is a need to look for a more efficient method for girls.

Background. The optimal body mass index (BMI) and fat mass index (FMI) values for a positive change or the lowest risk of no positive change after high-intensity interval training (HIIT) using the Tabata protocol remain unclear. This study is aimed at establishing these optimal BMI and FMI values for the lowest risk of failure of aerobic performance in adolescents. Methods. A 10-week HIIT programme was introduced into the physical education of 73 students. BMI was calculated using height and weight. Bioelectrical impedance analysis measured body fat, and the InBody apparatus generated the FMI. Based on BMI and FMI, the participants were divided into four groups. Pre- and post-HIIT intervention analyses were carried out using the Harvard step test, which was used to determine the physical efficiency index (PEI). Results. The Youden index confirmed that the risk of no positive effects in PEI was the lowest for the second BMI interval (19.01-22.00 kg/m2) and FMI Q 2 − 3 (7.96-8.91 kg/m2). The optimal BMI value for the lowest risk of no change in PEI was 20.60 kg/m2, and the optimal FMI value was 8.84 kg/m2. Conclusion. A comparison of the two indices shows that FMI had stronger effects on PEI than BMI. In addition, the model obtained for FMI had higher accuracy. Identifying at-risk individuals, those in need of improving health-related fitness (H-RF), and those with a low risk of poor H-RF allows for efficient planning of individual intervention services and training programmes.

This study aimed to investigate whether asymmetry of force, power, and tissue morphology are lower limbs (LL) injury risk factors in physically active adults. Fifty-eight men aged 23.8 ± 1.2 years and forty-seven women aged 23.3 ± 1.0 years were examined. Physical activity level was measured by the International Physical Activity Questionnaire, and injury data were collected with the Injury History Questionnaire. The countermovement jump was performed to evaluate force and power. LL tissue composition was evaluated by a bioimpedance analyzer. The symmetry indices were calculated. A comparison between injured and non-injured subjects in both sexes was conducted to determine indices associated with injuries. The symmetry indices cut-off points were calculated to establish values indicating a significant injury risk increase, and logistic regression was performed. The relative peak force asymmetry above 4.049% was associated with increased injury risk in men. The LL skeletal muscle mass asymmetry above 3.584% was associated with a higher injury risk in women. Increased asymmetry in indicated indices by 1% was associated with 19.8% higher injury risk in men and 82.6% in women. Asymmetry proved to be an injury risk factor. However, a more suitable index for men is relative peak force asymmetry, whereas LL skeletal muscle mass asymmetry is more suitable for women.

Background Body composition indices can be related to musculoskeletal injuries (MI), particularly in physically active groups. However, little is known about the accuracy of these diagnoses as potential predictors of musculoskeletal injuries. Therefore, this study aims to indicate the cut-off points of relative body mass (BMI), fat mass index (FMI), skeletal muscle mass (SMI), and muscle to fat ratio (MFR) and establish its reliability in injury prediction for physically active men and women. Methods The sample included 119 physically active individuals aged 23.72 ± 1.12 (66 men body height 1.79 ± 0.07 (m); body weight 80.51 ± 9.85 (kg) and 53 women body height 1.67 ± 0.08 (m); body weight 62 ± 10.72 (kg)), students at university of physical education in Poland. The participants’ physical activity was measured with the International Physical Activity Questionnaire (IPAQ). The relevance of body mass index (BMI), fat mass index (FMI), skeletal muscle mass index (SMI), and muscle to fat ratio (MFR) in detecting injury risk was examined. Musculoskeletal injuries during 1 year before examination were registered using a self-reporting questionnaire. The areas under the curve (AUC) and Youden Index in the receiver operating characteristic curve (ROC) were calculated. Results The cut-off points used to classify the indices among men were BMI = 24.38; FMI = 3.74; SMI = 16.40; MFR = 3.70; and for women BMI = 20.90; FMI = 4.17; SMI = 8.96; MFR = 1.67. Results suggested the greatest reliability in the prediction of musculoskeletal injuries among men had BMI (AUC = 0.623; Youden = 0.30) and SMI (AUC = 0.608; Youden = 0.23) whereas among women, MFR (AUC = 0.628; Youden = 0.29) and FMI (AUC = 0.614; Youden = 0.32). Conclusion BMI and SMI are the most appropriate indices to predict the risk of musculoskeletal injury in physically active men, whereas in women, MFR and FMI are more reliable. These results indicate that the indices with more muscle mass meaning are better in predicting injury among men. In contrast, indices with a higher contribution of fat are better for women. It indicates sex differentiation of injury risk conditions. Men should focus on developing muscle mass, whereas women should reduce body fat to decrease injury risk. However, widespread use seemed to be limited to the specific examined group. Therefore, cut-off points should be used with caution, and calculated values should be verified and confirmed in subsequent studies.