Background Concentrations of endogenous sex hormones fluctuate across the menstrual cycle (MC), which could have implications for exercise performance in women. At present, data are conflicting, with no consensus on whether exercise performance is affected by MC phase. Objective To determine the effects of the MC on exercise performance and provide evidence-based, practical, performance recommendations to eumenorrheic women. Methods This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four databases were searched for published experimental studies that investigated the effects of the MC on exercise performance, which included at least one outcome measure taken in two or more defined MC phases. All data were meta-analysed using multilevel models grounded in Bayesian principles. The initial meta-analysis pooled pairwise effect sizes comparing exercise performance during the early follicular phase with all other phases (late follicular, ovulation, early luteal, mid-luteal and late luteal) amalgamated. A more comprehensive analysis was then conducted, comparing exercise performance between all phases with direct and indirect pairwise effect sizes through a network meta-analysis. Results from the network meta-analysis were summarised by calculating the Surface Under the Cumulative Ranking curve (SUCRA). Study quality was assessed using a modified Downs and Black checklist and a strategy based on the recommendations of the Grading of Recommendations Assessment Development and Evaluation (GRADE) working group. Results Of the 78 included studies, data from 51 studies were eligible for inclusion in the initial pairwise meta-analysis. The three-level hierarchical model indicated a trivial effect for both endurance- and strength-based outcomes, with reduced exercise performance observed in the early follicular phase of the MC, based on the median pooled effect size (ES0.5 = − 0.06 [95% credible interval (CrI): − 0.16 to 0.04]). Seventy-three studies had enough data to be included in the network meta-analysis. The largest effect was identified between the early follicular and the late follicular phases of the MC (ES0.5 = − 0.14 [95% CrI: − 0.26 to − 0.03]). The lowest SUCRA value, which represents the likelihood that exercise performance is poor, or among the poorest, relative to other MC phases, was obtained for the early follicular phase (30%), with values for all other phases ranging between 53 and 55%. The quality of evidence for this review was classified as “low” (42%). Conclusion The results from this systematic review and meta-analysis indicate that exercise performance might be trivially reduced during the early follicular phase of the MC, compared to all other phases. Due to the trivial effect size, the large between-study variation and the number of poor-quality studies included in this review, general guidelines on exercise performance across the MC cannot be formed; rather, it is recommended that a personalised approach should be taken based on each individual's response to exercise performance across the MC.
The concept of personalized nutrition and exercise prescription represents a topical and exciting progression for the discipline given the large inter-individual variability that exists in response to virtually all performance and health related interventions. Appropriate interpretation of intervention-based data from an individual or group of individuals requires practitioners and researchers to consider a range of concepts including the confounding influence of measurement error and biological variability. In addition, the means to quantify likely statistical and practical improvements are facilitated by concepts such as confidence intervals (CIs) and smallest worthwhile change (SWC). The purpose of this review is to provide accessible and applicable recommendations for practitioners and researchers that interpret, and report personalized data. To achieve this, the review is structured in three sections that progressively develop a statistical framework. Section 1 explores fundamental concepts related to measurement error and describes how typical error and CIs can be used to express uncertainty in baseline measurements. Section 2 builds upon these concepts and demonstrates how CIs can be combined with the concept of SWC to assess whether meaningful improvements occur post-intervention. Finally, section 3 introduces the concept of biological variability and discusses the subsequent challenges in identifying individual response and non-response to an intervention. Worked numerical examples and interactive Supplementary Material are incorporated to solidify concepts and assist with implementation in practice.
Objective To conduct a systematic review and metaanalysis of the evidence on the effects of β-alanine supplementation on exercise capacity and performance. Design This study was designed in accordance with PRISMA guidelines. A 3-level mixed effects model was employed to model effect sizes and account for dependencies within data. Data sources 3 databases (PubMed, Google Scholar, Web of Science) were searched using a number of terms ('β-alanine' and 'Beta-alanine' combined with 'supplementation', 'exercise', 'training', 'athlete', 'performance' and 'carnosine'). Eligibility criteria for selecting studies Inclusion/ exclusion criteria limited articles to double-blinded, placebo-controlled studies investigating the effects of β-alanine supplementation on an exercise measure. All healthy participant populations were considered, while supplementation protocols were restricted to chronic ingestion. Cross-over designs were excluded due to the long washout period for skeletal muscle carnosine following supplementation. A single outcome measure was extracted for each exercise protocol and converted to effect sizes for meta-analyses. Results 40 individual studies employing 65 different exercise protocols and totalling 70 exercise measures in 1461 participants were included in the analyses. A significant overall effect size of 0.18 (95% CI 0.08 to 0.28) was shown. Meta-regression demonstrated that exercise duration significantly ( p=0.004) moderated effect sizes. Subgroup analyses also identified the type of exercise as a significant ( p=0.013) moderator of effect sizes within an exercise time frame of 0.5-10 min with greater effect sizes for exercise capacity (0.4998 (95% CI 0.246 to 0.753)) versus performance (0.1078 (95% CI −0.201 to 0.416)). There was no moderating effect of training status ( p=0.559), intermittent or continuous exercise ( p=0.436) or total amount of β-alanine ingested ( p=0.438). Co-supplementation with sodium bicarbonate resulted in the largest effect size when compared with placebo (0.43 (95% CI 0.22 to 0.64)). Summary/conclusions β-alanine had a significant overall effect while subgroup analyses revealed a number of modifying factors. These data allow individuals to make informed decisions as to the likelihood of an ergogenic effect with β-alanine supplementation based on their chosen exercise modality.
Swinton, PA, Lloyd, R, Keogh, JWL, Agouris, I, and Stewart, AD. A biomechanical comparison of the traditional squat, powerlifting squat, and box squat. J Strength Cond Res 26(7): 1805-1816, 2012. The purpose of this study was to compare the biomechanics of the traditional squat with 2 popular exercise variations commonly referred to as the powerlifting squat and box squat. Twelve male powerlifters performed the exercises with 30, 50, and 70% of their measured 1 repetition maximum (1RM), with instruction to lift the loads as fast as possible. Inverse dynamics and spatial tracking of the external resistance were used to quantify biomechanical variables. A range of significant kinematic and kinetic differences (p , 0.05) emerged between the exercises. The traditional squat was performed with a narrow stance, whereas the powerlifting squat and box squat were performed with similar wide stances (48.3 6 3.8, 89.6 6 4.9, 92.1 6 5.1 cm, respectively). During the eccentric phase of the traditional squat, the knee traveled past the toes resulting in anterior displacement of the system center of mass (COM). In contrast, during the powerlifting squat and box squat, a more vertical shin position was maintained, resulting in posterior displacements of the system COM. These differences in linear displacements had a significant effect (p , 0.05) on a number of peak joint moments, with the greatest effects measured at the spine and ankle. For both joints, the largest peak moment was produced during the traditional squat, followed by the powerlifting squat, then box squat. Significant differences (p , 0.05) were also noted at the hip joint where the largest moment in all 3 planes were produced during the powerlifting squat. Coaches and athletes should be aware of the biomechanical differences between the squatting variations and select according to the kinematic and kinetic profile that best match the training goals.
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