Normative data for the squat, bench press and deadlift exercises in powerlifting: Data from 809,986 competition entries.

OBJECTIVES: Strength assessment and comparison to normative values are an important benchmarking tool in human health and performance. However, population specific normative data are several decades old, lack information about adolescent and adult strength levels and are not representative of the strength levels of strength trained individuals. The purpose of this study was to develop contemporary strength norms for the squat, bench press, and deadlift using powerlifters competing in un-equipped, drug-tested competitions. DESIGN: Retrospective cross-sectional analysis. METHODS: Retrospective data from global drug-tested, unequipped powerlifting competitions were collated with 809,986 samples (571,650 males, 238,336 females) included. Strength was assessed according to sex, United Nations age classifications, and competitive powerlifting weight class. Strength was expressed relatively (ratio of weight lifted/bodyweight) and computed for the 10th-90th percentile for each of the above categories. RESULTS: Relative strength was greatest for young adults (18-35 years; 90th percentile for squat [male: 2.83 × bodyweight, female: 2.26], bench press [male: 1.95, female: 1.35], deadlift [male: 3.25, female: 2.66]) before declining thereafter for all three exercises. Although lower than their younger counterparts, very old adults (>80 years) had 90th percentile data for the squat of male: 1.72 and female: 1.01, bench press: male: 1.31 and female: 0.92, and deadlift: male: 2.30 and female: 1.68. CONCLUSIONS: These findings provide a comprehensive, accurate and precise representation of strength for drug-tested, unequipped powerlifters in each category and serve as a point of reference for other trained population groups. To facilitate uptake and ease of comparison, we have developed a freely available online tool (www.thestrengthinitiative.com).

Hamstring Injuries, From the Clinic to the Field: A Narrative Review Discussing Exercise Transfer.

PURPOSE: The optimal approach to hamstring training is heavily debated. Eccentric exercises reduce injury risk; however, it is argued that these exercises transfer poorly to improved hamstring function during sprinting. Some argue that other exercises, such as isometric exercises, result in better transfer to running gait and should be used when training to improve performance and reduce injury risk. Given the performance requirements of the hamstrings during the terminal swing phase, where they are exposed to high strain, exercises should aim to improve the torque production during this phase. This should improve the hamstrings' ability to resist overlengthening consequently, improving performance and limiting strain injury. Most hamstring training studies fail to assess running kinematics postintervention. Of the limited evidence available, only eccentric exercises demonstrate changes in swing-phase kinematics following training. Studies of other exercise modalities investigate effects on markers of performance and injury risk but do not investigate changes in running kinematics. CONCLUSIONS: Despite being inconsistent with principles of transfer, current evidence suggests that eccentric exercises result in transfer to swing-phase kinematics. Other exercise modalities may be effective, but the effect of these exercises on running kinematics is unknown.

Study protocol - assessing parkrun for walking rehabilitation for people living with, and beyond, cancer: acceptability, adherence, social support and physical function.

INTRODUCTION: Due to a variety of barriers, the majority of cancer survivors do not do enough physical activity to meet current recommendations. This study will assess the feasibility of participation in parkrun walk-run events as a novel mode of community rehabilitation exercise. METHODS: This protocol describes a single-arm intervention study with participants acting as their own controls. The study accepts adults diagnosed with any type of cancer, undergoing treatment or in remission. Participants must be able to walk and have medical clearance to exercise. A sample of 100 participants will be recruited across the Sunshine Coast over two years. Data will be collected over 9-months at 4 time points: Baseline (T1); after 4-weeks of usual daily activities and cancer management prior to parkrun participation(T2); after a 6-month parkrun intervention (T3); at 2-month follow-up (T4). The primary objectives are to assess the acceptability of, and adherence to, parkrun as rehabilitation exercise. Secondary outcomes include wellness, health-related quality of life, anxiety, depression, mood, physical function, parkrun metrics, dietary intake, and diet and exercise behaviour. CONCLUSION: This study will be the first to examine the long-term effects of parkrun as a cancer rehabilitation modality with regard to physical function, psychosocial outcomes and dietary intake. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTRN12623000473662 registered 09/05/2023.Approved by UniSC Human Research Ethics Committee (A221828) and the UK parkrun Research Board. Original protocol. Authors SB, RB, HHW, MM, YK.

Meta-analysis prediction intervals are under reported in sport and exercise medicine.

AIM: Prediction intervals are a useful measure of uncertainty for meta-analyses that capture the likely effect size of a new (similar) study based on the included studies. In comparison, confidence intervals reflect the uncertainty around the point estimate but provide an incomplete summary of the underlying heterogeneity in the meta-analysis. This study aimed to estimate (i) the proportion of meta-analysis studies that report a prediction interval in sports medicine; and (ii) the proportion of studies with a discrepancy between the reported confidence interval and a calculated prediction interval. METHODS: We screened, at random, 1500 meta-analysis studies published between 2012 and 2022 in highly ranked sports medicine and medical journals. Articles that used a random effect meta-analysis model were included in the study. We randomly selected one meta-analysis from each article to extract data from, which included the number of estimates, the pooled effect, and the confidence and prediction interval. RESULTS: Of the 1500 articles screened, 866 (514 from sports medicine) used a random effect model. The probability of a prediction interval being reported in sports medicine was 1.7% (95% CI = 0.9%, 3.3%). In medicine the probability was 3.9% (95% CI = 2.4%, 6.6%). A prediction interval was able to be calculated for 220 sports medicine studies. For 60% of these studies, there was a discrepancy in study findings between the reported confidence interval and the calculated prediction interval. Prediction intervals were 3.4 times wider than confidence intervals. CONCLUSION: Very few meta-analyses report prediction intervals and hence are prone to missing the impact of between-study heterogeneity on the overall conclusions. The widespread misinterpretation of random effect meta-analyses could mean that potentially harmful treatments, or those lacking a sufficient evidence base, are being used in practice. Authors, reviewers, and editors should be aware of the importance of prediction intervals.