A very limited amount of research has examined intermittent fasting (IF) programs, such as time-restricted feeding (TRF), in active populations. Our objective was to examine the effects of TRF, with or without β-hydroxy β-methylbutyrate (HMB) supplementation, during resistance training (RT). This study employed a randomized, placebo-controlled, reduced factorial design and was double-blind with respect to supplementation in TRF groups. Resistance-trained females were randomly assigned to a control diet (CD), TRF, or TRF plus 3 g/d HMB (TRF_HMB). TRF groups consumed all calories between 1200 h and 2000 h, whereas the CD group ate regularly from breakfast until the end of the day. All groups completed 8 wk of supervised RT and consumed supplemental whey protein. Body composition, muscular performance, dietary intake, physical activity, and physiological variables were assessed. Data were analyzed prior to unblinding using mixed models and both intention-to-treat (ITT) and per protocol (PP) frameworks. Forty participants were included in ITT, and 24 were included in PP. Energy and protein intake (1.6 g/kg/d) did not differ between groups despite different feeding durations (TRF and TRF_HMB: ∼7.5 h/d; CD: ∼13 h/d). Comparable fat-free mass (FFM) accretion (+2% to 3% relative to baseline) and skeletal muscle hypertrophy occurred in all groups. Differential effects on fat mass (CD: +2%; TRF: −2% to −4%; TRF_HMB: −4% to −7%) were statistically significant in the PP analysis, but not ITT. Muscular performance improved without differences between groups. No changes in physiological variables occurred in any group, and minimal side effects were reported. IF, in the form of TRF, did not attenuate RT adaptations in resistance-trained females. Similar FFM accretion, skeletal muscle hypertrophy, and muscular performance improvements can be achieved with dramatically different feeding programs that contain similar energy and protein content during RT. Supplemental HMB during fasting periods of TRF did not definitively improve outcomes. This study was prospectively registered at clinicaltrials.gov as NCT03404271.

Krzyszkowski, J, Chowning, LD, and Harry, JR. Phase-specific predictors of countermovement jump performance that distinguish good from poor jumpers. J Strength Cond Res 36(5): 1257–1263, 2022—The modified-reactive strength index (RSImod) is commonly examined during the countermovement vertical jump (CMJ) to assess neuromuscular characteristics (i.e., explosiveness, fatigue, adaptation, etc.) of an athlete. However, both phase-specific variables explaining RSImod and corresponding differences between good and poor jumpers are not well understood in trained populations. This study sought to (a) identify predictors of RSImod during the CMJ based on phase-specific temporal and rate of force development (RFD) variables, and (b) identify differences in those predictors between performers with high and low RSImod performances from a sample of collegiate male basketball players (n = 22; 20 ± 2 years; 1.99 ± 0.06 month; 93.8 ± 7.5 kg). Subjects performed 3 maximal effort CMJ trials while ground reaction force data was recorded using 2 force platforms. Phase-specific temporal and RFD variables were calculated and entered into separate stepwise regression models using backward elimination to identify predictors RSImod. Individuals were then categorized into high (n = 11; RSImod = 0.68 ± 0.10) and low (n = 11; RSImod = 0.48 ± 0.04) RSImod groups according to the overall median RSImod (RSImod = 0.55). Independent t-tests (α = 0.05) were conducted and supplemented by Cohen's d effect sizes (d ≥ 1.2, large) to compare groups relative to significant predictors identified by the linear regression models and related variables. The temporal regression model (R ² = 0.530) retained unloading time and concentric time, whereas the RFD regression model (R ² = 0.429) retained unloading RFD and braking RFD. The high RSImod group exhibited significantly greater RSImod scores (d = 2.51, p < 0.001) and jump heights (d = 1.58, p < 0.001), shorter times to takeoff (d = 1.27, p = 0.007) and concentric times (d = 1.51, p = 0.002), and a greater braking RFD (d = 1.41, p = 0.005) than the low RSImod group. Individuals targeting enhanced CMJ performance may consider exploring strategies or interventions to develop quicker unloading and concentric phases and increasing eccentric RFD abilities.

Harry, JR, Blinch, J, Barker, LA, Krzyszkowski, J, and Chowning, L. Low-pass filter effects on metrics of countermovement vertical jump performance. J Strength Cond Res 36(5): 1459–1467, 2022—Countermovement vertical jump (CMVJ) studies using ground reaction force (GRF) data analyze either unfiltered (i.e., raw) or filtered data while providing little-to-no justification for the selected filtering process. Inappropriate filter choices can lead to inaccurate study results and erroneous interpretations. We examined the effects of not filtering GRF data in comparison with filtering data with various objectively and subjectively selected cutoff frequencies. Twenty-one collegiate male basketball players completed 3 maximal-effort CMVJ trials while GRF data were obtained from 2 force platforms. Countermovement vertical jump performance, explosiveness, power output, and neuromuscular function variables were compared among the following methods using one-way repeated-measures analyses of variance (α = 0.05): no filtering (raw data), a standard 50-Hz cutoff (50 Hz), a visually determined cutoff frequency describing the frequency band containing the majority of the summed (visual inspection 1) or not-summed (visual inspection 2) GRF signal's frequency content, filtering the summed (99% signal power 1) or not-summed (99% signal power 2) GRF using a cutoff frequency retaining 99% of the signal power. The raw data method produced significantly shorter concentric phase times and significantly greater center of mass flight heights (∼3%), modified reactive strength indices (RSI_MOD; ∼4%), power outputs (∼6%), and push-off distances (∼4%) than 99% signal power 1 and 2 (p < 0.05). Discrete GRF and phase-specific yank magnitudes were not different among methods (p ≥ 0.05). Importantly, no differences were detected between the raw data and 50 Hz methods for any variable (p > 0.05). Low-pass filtering is not necessary when analyzing GRF data from the CMVJ. However, a low-pass filter with a 50-Hz cutoff can remove noise without altering results when compared with raw data. Explicit methodological descriptions of filtering processes should always be provided to improve the integrity of future CMVJ analyses, comparisons among various studies' results, or both.

Conflicting methodologies are used to define certain countermovement vertical jump (CMVJ) phases, which limits the identification of performance-enhancing factors (e.g., rate of force development). Purpose: We (a) utilized a joint power approach to define CMVJ phases that accurately describe body weight unloading (i.e., unweighting) and eccentric (i.e., braking) actions, which were combined with the robustly defined concentric (i.e., propulsion) phase, and (b) determined whether the phases can be identified using only ground reaction force (GRF) data. Methods: Twenty-one men performed eight maximal CMVJs while kinematic and GRF data were obtained. Hip, knee, and ankle joint powers were calculated by multiplying net joint moments (obtained using inverse dynamics) by joint angular velocities. The net sum of the joint powers (JP_SUM) was calculated to define phases by the preeminence of negative (i.e., net eccentric actions) or positive (i.e., net concentric actions) power where appropriate. Unloading, eccentric, and concentric phases were identified using JP_SUM and linked to GRF and center of mass velocity features. Results: Bland and Altman plots of the bias and 95% confidence intervals for the limits of agreement (LOA), intraclass correlation coefficients (ICC), and coefficients of variation (CV) indicated precise agreement for detecting the unloading (bias, 0.060 s; LOA, −0.110 to 0.229 s) and eccentric (bias, 0.012 s; LOA, −0.010 to 0.040 s) phases with moderate (ICC, 0.578; CV, 40.72%) and excellent (ICC, 0.993; CV, 2.18%) reliability, respectively. The eccentric phase should be divided into yielding (eccentric actions while accelerating downward) and braking (eccentric actions while decelerating downward) subphases for detailed assessments. Conclusion: CMVJ phases defined by combining joint and center of mass mechanics can be detected using only force platform data, enabling functionally relevant CMVJ assessments using instrumentation commonly available to practitioners.

Anecdotal reports suggest children with autism spectrum disorder (ASD) ambulate differently than peers with typical development (TD). Little empirical evidence supports these reports. Children with ASD exhibit delayed motor skills, and it is important to determine whether or not motor movement deficits exist during walking. The purpose of the study was to perform a comprehensive lower-extremity gait analysis between children (aged 5–12 years) with ASD and age- and gender-matched-samples with TD. Gait parameters were normalized to 101 data points and the gait cycle was divided into seven sub-phases. The Model Statistic procedure was used to test for statistical significance between matched-pairs throughout the entire gait cycle for each parameter. When collapsed across all participants, children with ASD exhibited large numbers of significant differences (p < 0.05) throughout the gait cycle in hip, knee, and ankle joint positions as well as vertical and anterior/posterior ground reaction forces. Children with ASD exhibited unique differences throughout the gait cycle, which supports current literature on the heterogeneity of the disorder. The present work supports recent findings that motor movement differences may be a core symptom of ASD. Thus, individuals may benefit from therapeutic movement interventions that follow precision medicine guidelines by accounting for individual characteristics, given the unique movement differences observed.