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Background No previous systematic review has quantitatively examined the association between muscular fitness during childhood and adolescence and health parameters later in life. Objective The aim was to systematically review and meta-analyze the current evidence for a prospective association between muscular fitness in childhood and adolescence and future health status. Methods Two authors systematically searched MEDLINE, EMBASE and SPORTDiscus electronic databases and conducted manual searching of reference lists of selected articles. Relevant articles were identified by the following criteria: apparently healthy children and adolescents aged 3–18 years with muscular fitness assessed at baseline (e.g., handgrip, standing long jump, sit-ups, among others), and a follow-up period of ≥ 1 year. The outcome measures were anthropometric and adiposity measurements and cardiometabolic, bone and musculoskeletal health parameters. Two authors independently extracted data. Results Thirty studies were included in the meta-analysis, yielding a total of 21,686 participants. The meta-analysis found a significant, moderate-large ( p  < 0.05) effect size between muscular fitness at baseline and body mass index ( r  = − 0.14; 95% confidence interval (CI) − 0.21 to − 0.07), skinfold thickness ( r  = − 0.32; 95% CI − 0.40 to − 0.23), homeostasis model assessment estimated insulin resistance ( r  = − 0.10; 95% CI − 0.16 to − 0.05), triglycerides ( r  = − 0.22; 95% CI − 0.30 to − 0.13), cardiovascular disease risk score ( r  = − 0.29; 95% CI − 0.39 to − 0.18), and bone mineral density ( r  = 0.166; 95% CI 0.086 to 0.243) at follow-up. Conclusion A prospective negative association was observed between muscular fitness in childhood/adolescence and adiposity and cardiometabolic parameters in later life, together with a positive association for bone health. There is inconclusive evidence for low back pain benefits.

The aim of this study is to conduct a systematic review with meta-analysis to explore the effects of plyometric jump training (PJT) on the physical fitness of individual sport athletes (ISA). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched through PubMed, Web of Science, and SCOPUS electronic databases. We included controlled studies that incorporated a PJT intervention among ISA (with no restriction for age or sex), that included a pre-to-post intervention assessment of physical fitness (e.g., sprint; jump). From the included studies, relevant data (e.g., PJT and participants characteristics) was extracted. We assessed the methodological quality of the included studies using the PEDro scale. Using a random-effects model, meta-analyses for a given outcome was conducted. Means and standard deviations for a measure of pre-post-intervention physical fitness from the PJT and control groups were converted to Hedges' g effect size (ES). Heterogeneity was assessed using the statistic. The risk of bias was explored using the extended Egger's test. The statistical significance threshold was set at < 0.05. Moderator analyses were conducted according to the sex, age and sport background of the athletes. Twenty-six studies of moderate-high methodological quality were included (total participants, = 667). Compared to controls, PJT improved vertical jump (ES = 0.49; < 0.001; = 0.0%), linear sprint (ES = 0.23; = 0.032; = 10.9%), maximal strength (ES = 0.50; < 0.001; = 0.0%) and endurance performance (ES = 0.30; = 0.028; = 11.1%). No significant effect was noted for sprint with change of direction (ES = 0.34; = 0.205; = 70.9%). Athlete's sex, age and sport background had no modulator role on the effect of PJT on vertical jump, linear sprint, maximal strength and endurance performance. Among the included studies, none reported adverse effects related to the PJT intervention. PJT induces small improvements on ISA physical fitness, including jumping, sprinting speed, strength and endurance.

This study aimed to evaluate the concurrent validity of two different inertial measurement units for measuring spatiotemporal parameters during running on a treadmill, by comparing data with a high-speed video analysis (VA) at 1,000 Hz. Forty-nine endurance runners performed a running protocol on a treadmill at comfortable velocity (i.e., 3.25 ± 0.36 m.s-1). Those wearable devices (i.e., Stryd™ and RunScribe™ systems) were compared to a high-speed VA, as a reference system for measuring spatiotemporal parameters (i.e. contact time [CT], flight time [FT], step frequency [SF] and step length [SL]) during running at comfortable velocity. The pairwise comparison revealed that the Stryd™ system underestimated CT (5.2%, p < 0.001) and overestimated FT (15.1%, p < 0.001) compared to the VA; whereas the RunScribe™ system underestimated CT (2.3%, p = 0.009). No significant differences were observed in SF and SL between the wearable devices and VA. The intra class correlation coefficient (ICC) revealed an almost perfect association between both systems and high-speed VA (ICC > 0.81). The Bland-Altman plots revealed heteroscedasticity of error (r2 = 0.166) for the CT from the Stryd™ system, whereas no heteroscedasticity of error (r2 < 0.1) was revealed in the rest of parameters. In conclusion, the results obtained suggest that both foot pods are valid tools for measuring spatiotemporal parameters during running on a treadmill at comfortable velocity. If the limits of agreement of both systems are considered in respect to high-speed VA, the RunScribe™ seems to be a more accurate system for measuring temporal parameters and SL than the Stryd™ system.

Mechanical power may act as a key indicator for physiological and mechanical changes during running. In this scoping review, we examine the current evidences about the use of power output (PW) during endurance running and the different commercially available wearable sensors to assess PW. The Boolean phrases endurance OR submaximal NOT sprint AND running OR runner AND power OR power meter, were searched in PubMed, MEDLINE, and SCOPUS. Nineteen studies were finally selected for analysis. The current evidence about critical power and both power-time and power-duration relationships in running allow to provide coaches and practitioners a new promising setting for PW quantification with the use of wearable sensors. Some studies have assessed the validity and reliability of different available wearables for both kinematics parameters and PW when running but running power meters need further research before a definitive conclusion regarding its validity and reliability.

Background Strong evidence shows that physical inactivity increases the risk of many adverse health conditions, including major non-communicable diseases, such as cardiovascular disease (CVD), metabolic syndrome, and breast and colon cancers, and shortens life expectancy. We aimed to determine the effects of moderate (MCT)- versus high-intensity interval training (HIT) on vascular function parameters in physically inactive adults. We hypothesized that individualized HIT prescription would improve the vascular function parameters more than the MCT in a greater proportion of individuals. Methods Twenty-one inactive adults were randomly allocated to receive either MCT group (60–75% of their heart rate reserve, [HRR] or HIT group (4 min at 85–95% of peak HRR), 3 days a week for 12 weeks. Vascular function (brachial artery flow-mediated dilation, FMD [%], normalized brachial artery flow-mediated dilation, FMDn [%], aortic pulse wave velocity, PWV [m·s − 1 ], AIx, augmentation index: aortic and brachial [%]), were measured at baseline and over 12 weeks of training. In order for a participant to be considered a responder to improvements in vascular function parameters (FMDn and PWV), the typical error was calculated in a favorable direction. Results FMD changed by − 1.0% (SE 2.1, d  = 0.388) in the MCT group, and + 1.8% (SE 1.8, d  = 0.699) in the HIT group (no significant difference between groups: 2.9% [95% CI, − 3.0 to 8.8]. PWV changed by + 0.1 m·s − 1 (SE 0.2, d  = 0.087) in the MCT group but decreased by − 0.4 m·s − 1 in the HIT group (SE 0.2, d  = 0.497), with significant difference between groups: − 0.4 [95% CI, − 0.2 to − 0.7]. There was not a significant difference in the prevalence of no-responder for FMD (%) between the MCT and HIT groups (66% versus 36%, P  = 0.157). Regarding PWV (m·s − 1 ), an analysis showed that the prevalence of no-responder was 77% (7 cases) in the MCT group and 45% (5 cases) in the HIT group ( P  = 0.114). Conclusions Under the conditions of the present study, both groups experienced changed in vascular function parameters. Compared to MCT group, HIT is more efficacious for improving FMD and decreasing PWV, in physically inactive adults. Trial registration ClinicalTrials.gov NCT02738385 registered on 23 March 2016.

To investigate the effects of a six-week plyometric training and creatine supplementation intervention on maximal-intensity and endurance performance in female soccer players during in-season training. Randomized, double-blind, placebo-controlled trial. Young (age 22.9±2.5y) female players with similar training load and competitive background were assigned to a plyometric training group receiving placebo (PLACEBO, n=10), a plyometric training group receiving creatine supplementation (CREATINE, n=10) or a control group receiving placebo without following a plyometric program (CONTROL, n=10). Athletes were evaluated for jumping, maximal and repeated sprinting, endurance and change-of-direction speed performance before and after six weeks of training. After intervention the CONTROL group did not change, whereas both plyometric training groups improved jumps (ES=0.25–0.49), sprint (ES=0.35–0.41), repeated sprinting (ES=0.48–0.55), endurance (ES=0.32–0.34) and change-of-direction speed performance (ES=0.46–0.55). However, the CREATINE group improved more in the jumps and repeated sprinting performance tests than the CONTROL and the PLACEBO groups. Adaptations to plyometric training may be enhanced with creatine supplementation.

Basketball demands a sophisticated blend of tactical, technical, physical, and psychological skills, and various methods have been proposed to prepare players for these demands, including resistance training to enhance strength, power, speed, agility, and endurance. Complex training (CT) integrates diverse strength training methodologies by combining heavy-resistance exercises (e.g., squat at 90% of one repetition maximum) with high-velocity movements or plyometrics, both sharing the same biomechanical pattern. However, the optimal application of CT in basketball remains uncertain due to diverse protocols and a lack of consensus in the literature. The aim of this systematic review was to evaluate the acute and chronic effects of CT interventions on physical fitness performance in basketball players and identify the most effective characteristics of moderators. Methods: A bibliographic search was conducted using PubMed, SCOPUS, and Web of Science databases following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines using the PICOS strategy. Results: Fourteen studies met the inclusion criteria, three articles analyzed acute effects, and thirteen analyzed chronic effects. The total number of participants in the studies analyzing acute effects was 50, while for studies examining chronic effects, it was 362. Conclusions: Acutely, CT triggers post-activation potentiation and enhances sprint performance when coupled with brief rest intervals. Over time, these acute improvements contribute to more substantial, long-lasting benefits. Chronic effects of CT improve strength, as evidenced by enhanced 1 RM performance, jumps, sprints, and core muscle strength.

Running as exercise may be performed either on an outdoor surface or treadmill surface. However, previous research has indicated that the nature of both the surfaces differ significantly and therefore the training outcomes from running in these surfaces may also vary. Therefore, the aim of this pilot study was to compare the effects of 6-weeks of supervised outdoor running (OT) treadmill running (TT) on physical fitness and body composition in recreationally active young males. Participants (age: 19.82 ± 1.28 years, height: 172.6 ± 4.9 cm, body mass: 64.3 ± 8.7 kg) were randomly assigned to OT ( = 14) or TT ( = 14), and assessed for physical fitness, ., 50 m sprint, cardiorespiratory endurance ( ., 1,600 m run time-trial), standing long jump (SLJ), flexibility ( ., sit-and-reach test), and upper-body muscle endurance ( ., push-ups repetitions), alongside body composition, ., body mass, body mass index (BMI), fat percentage, fat free mass, and leg skeletal muscle mass (SMM). A two (pre-post intervention) by two (OT, TT) mixed ANOVA analysed exercise-specific effects. For significant group-by-time interactions, Bonferroni adjusted paired (within-group) and independent (between-group comparisons at post) t-tests were used for post-hoc analyses. Significant time-effect was found in all physical fitness variables (all < 0.001, η = 0.67-0.91), body mass ( = 0.23, η = 0.18), BMI ( = 0.009, η = 0.24), body fat percentage ( = 0.001, η = 0.38), and leg SMM ( = 0.002-0.007, η = 0.25-0.33). Significant group-by-time interaction was found for 50 m sprint ( = < 0.001, η = 0.74), 1,600 m run ( = 0.001, η = 0.35), and SLJ ( < 0.001, η = 0.43), favouring OT. Group-specific post-hoc tests showed improvements in all physical fitness variables after OT ( = < 0.001-0.001, = 0.69-2.32, %Δ = 3.0-12.4) and TT ( = < 0.001-0.017, = 0.15-0.65, %Δ = 0.9-11.7), and fat percentage after OT and TT ( = 0.002-0.041, g = 0.14-0.26, %Δ = 4.3-6.0). However, leg SMM decreased in TT ( = 0.001-0.004, g = 0.14-0.15, %Δ = 6.2-6.7). Both OT and TT improved physical fitness and decreased fat percentage. However, compared to TT, the OT intervention preserved leg SMM and induced greater physical fitness improvements.

ObjectiveTo determine if the combination of aerobic and resistance exercise is superior to aerobic exercise alone for the health of obese children and adolescents.DesignSystematic review with meta-analysis.Data sourcesComputerised search of 3 databases (MEDLINE, EMBASE, and Cochrane Controlled Trials Registry).Eligibility criteria for selecting studiesStudies that compared the effect of supervised concurrent exercise versus aerobic exercise interventions, with anthropometric and metabolic outcomes in paediatric obesity (6–18 years old). The mean differences (MD) of the parameters from preintervention to postintervention between groups were pooled using a random-effects model.Results12 trials with 555 youths were included in the meta-analysis. Compared with aerobic exercise alone, concurrent exercise resulted in greater reductions in body mass (MD=−2.28 kg), fat mass (MD=−3.49%; and MD=−4.34 kg) and low-density lipoprotein cholesterol (MD=−10.20 mg/dL); as well as greater increases in lean body mass (MD=2.20 kg) and adiponectin level (MD=2.59 μg/mL). Differences were larger for longer term programmes (>24 weeks).SummaryConcurrent aerobic plus resistance exercise improves body composition, metabolic profiles, and inflammatory state in the obese paediatric population.Trial registration numberCRD42016039807.

Background Diabetes mellitus (DM) has glucose variability that is of such relevance that the appearance of vascular complications in patients with DM has been attributed to hyperglycemic and dysglycemic events. It is known that T1D patients mainly have glycemic variability with a specific oscillatory pattern with specific circadian characteristics for each patient. However, it has not yet been determined whether an oscillation pattern represents the variability of glycemic in T2D. This is why our objective is to determine the characteristics of glycemic oscillations in T2D and generate a robust predictive model. Results Showed that glycosylated hemoglobin, glycemia, and body mass index were all higher in patients with T2D than in controls (all p < 0.05). In addition, time in hyperglycemia and euglycemia was markedly higher and lower in the T2D group (p < 0.05), without significant differences for time in hypoglycemia. Standard deviation, coefficient of variation, and total power of glycemia were significantly higher in the T2D group than Control group (all p < 0.05). The oscillatory patterns were significantly different between groups (p = 0.032): the control group was mainly distributed at 2–3 and 6 days, whereas the T2D group showed a more homogeneous distribution across 2–3-to-6 days. Conclusions The predictive model of glycemia showed that it is possible to accurately predict hyper- and hypoglycemia events. Thus, T2D patients exhibit specific oscillatory patterns of glycemic control, which are possible to predict. These findings may help to improve the treatment of DM by considering the individual oscillatory patterns of patients.