The Resistance Training Dose-Response: Meta-Regressions Exploring the Effects of Weekly Volume and Frequency on Muscle Hypertrophy and Strength Gain

Background: Weekly set volume and frequency are used to manipulate resistance training (RT) dosage. Previous research has identified higher weekly set volume as enhancing muscle hypertrophy and strength gains, but the nature of the dose-response relationship still needs to be investigated. Mixed evidence exists regarding the effects of higher weekly frequency. Objective: Before meta-analyzing the volume and frequency research, all contributing RT sets were classified as direct or indirect, depending on their specificity to the hypertrophy/strength measurement. Then, weekly set volume/frequency for indirect sets was quantified as 1 for ‘total,’ 0.5 for ‘fractional,’ and 0 for ‘direct.’ A series of multi-level meta-regressions were performed for muscle hypertrophy and strength, utilizing 67 total studies of 2,058 participants. All models were adjusted for the duration of the intervention and training status. Results: The relative evidence for the ‘fractional’ quantification method was strongest; therefore, this quantification method was used for the primary meta-regression models. The posterior probability of the marginal slope exceeding zero for the effect of volume on both hypertrophy and strength was 100%, indicating that gains in muscle size and strength increase as volume increases. However, both best fit models suggest diminishing returns, with the diminishing returns for strength being considerably more pronounced. The posterior probability of the marginal slope exceeding zero for frequency’s effect on hypertrophy was less than 100%, indicating compatibility with negligible effects. In contrast, the posterior probability for strength was 100%, suggesting strength gains increase with increasing frequency, albeit with diminishing returns. Conclusions: Distinguishing between direct and indirect sets appears essential for predicting adaptations to a given RT protocol, such as using the ‘fractional’ quantification method. This method’s dose-response models revealed that volume and frequency have unique dose-response relationships with each hypertrophy and strength gain. The dose-response relationship between volume and hypertrophy appears to differ from that with strength, with the latter exhibiting more pronounced diminishing returns. The dose-response relationship between frequency and hypertrophy appears to differ from that with strength, as only the latter exhibits consistently identifiable effects

Is There Too Much of a Good Thing? Meta-Regressions of the Effect of Per-Session Volume on Hypertrophy and Strength

Background: Recent research has quantified the dose-response relationship between weekly resistance training set volume and muscle hypertrophy and strength gains. However, the nature of the dose-response of per-session set volume remains underexplored.  Objective: Before meta-analyzing, all contributing sets were classified as direct or indirect, depending on their specificity to the measurement. Then, per-session set volume for indirect sets was quantified as 1 for ‘total,’ 0.5 for ‘fractional,’ and 0 for ‘direct.’ A series of multi-level meta-regressions were performed for muscle hypertrophy and strength, with all models adjusted for intervention duration and training status. The point of undetectable outcome superiority (PUOS) was identified as the per-session set volume in which additional sets did not result in a >50% likelihood of the difference in hypertrophy or strength gain exceeding the smallest detectable effect size.  Results: The ‘direct’ and ‘fractional’ quantification methods provided the strongest relative evidence for strength and hypertrophy, respectively; thus, these quantification methods were used for the primary meta-regression models. The posterior probability of the marginal slope exceeding zero for the effect of per-session volume on both strength and hypertrophy was 100%, indicating positive dose-response relationships between per-session set volume and hypertrophy and strength gains. However, both best fit models suggest diminishing returns as per-session set volume increases, with the PUOS occurring at ~2 ‘direct’ sets for strength and ~11 ‘fractional’ sets for hypertrophy. Notably, the ‘direct’ set model for strength gains suggests more strongly diminishing returns compared to the ‘fractional’ set model for hypertrophy. Conclusions: There is a positive dose-response relationship between per-session volume with both strength and hypertrophy; however, to quantify the dose-response relationship, it is paramount to distinguish between ‘fractional’ and ‘direct’ set counting methods. Furthermore, the relationship exhibits diminishing returns for both outcomes, which appear to manifest more strongly for strength gains compared to hypertrophy. While the available evidence indicates a PUOS of ~2 and ~11 sets per session for strength gain and hypertrophy, respectively, there is insufficient data with very high per-session set volumes. Therefore,  it is unclear whether there is a point in which additional per-session sets attenuate adaptations, or if even higher per-session set volumes could be potentially beneficial; thus, the PUOS should be interpreted cautiously

Exploring the Dose-Response Relationship Between Estimated Resistance Training Proximity to Failure, Strength Gain, and Muscle Hypertrophy : A Series of Meta-Regressions

Background: The proximity to failure in which sets are terminated has gained attention in the scientific literature as a potentially key resistance training variable. Multiple meta-analyses have directly (i.e., failure versus not to failure) or indirectly (e.g., velocity loss, alternative set structures) evaluated the effect of proximity to failure on strength and muscle hypertrophy outcomes categorically; however, the dose response effects of proximity to failure have not been analyzed collectively in a continuous manner. Objective: To meta-analyze the aforementioned areas of relevant research, proximity to failure was quantified as the number of repetitions in reserve (RIR). Importantly, the RIR associated with each effect in the analysis was estimated based on the available descriptions of the training interventions in each study. Data were extracted and a series of exploratory multi-level meta-regressions were performed for outcomes related to both strength and muscle hypertrophy. A range of sensitivity analyses were also performed. All models were adjusted for the effects of load, method of volume equating, duration of intervention, and training status. Results: The best fit models for both strength and muscle hypertrophy outcomes demonstrated modest quality of overall fit. In all of the best-fit models for strength, the confidence intervals of the marginal slopes for estimated RIR contained a null point estimate, indicating a negligible relationship with strength gains. However, in all of the best-fit models for muscle hypertrophy, the marginal slopes for estimated RIR were negative and their confidence intervals did not contain a null point estimate, indicating that changes in muscle size increased as sets were terminated closer to failure. Conclusions: The dose-response relationship between proximity to failure and strength gain appears to differ from the relationship with muscle hypertrophy, with only the latter being meaningfully influenced by RIR. Strength gains were similar across a wide range of RIR, while muscle hypertrophy improves as sets are terminated closer to failure. Considering the RIR estimation procedures used, however, the exact relationship between RIR and muscle hypertrophy and strength remains unclear. Researchers and practitioners should be aware that optimal proximity to failure may differ between strength and muscle hypertrophy outcomes, but caution is warranted when interpreting the present analysis due to its exploratory nature. Future studies deliberately designed to explore the continuous nature of the dose-response effects of proximity to failure in large samples should be considered

Mixing Up Muscle Lengths: The Effects of Training at Different Muscle Lengths in the Elbow Flexors

PURPOSE: This repeated measures within-participant unilateral design study investigated the effect of resistance training with the peak torque occurring at only longer muscle lengths (LONG) to training with the peak torque occurring at a mixture of long and short muscle lengths (MIXED). METHODS: 7 recreationally trained males (n=5) and females (n=2) trained for eight weeks, with limbs randomized to either LONG or MIXED conditions. The repeated measures design required participants to repeat the 8 week training after a 6-8 week washout period, which effectively created observations equivalent to  sample size of 14. In the LONG condition, participants performed six sets of seated lengthened cable curls to momentary failure with 3 minutes of interset rest each session. The MIXED condition performed three sets of seated lengthened cable curls and three sets of standing shortened cable curls to momentary failure with 3 minutes of interset rest each session. Elbow flexor cross-sectional area (CSA) and regional muscle thickness (MT) were assessed via panoramic b-mode ultrasonography at Pre and Post testing. Dynamic strength, isometric strength, and arm circumference were also assessed at Pre and Post testing. Session rating of perceived exertion (sRPE) and perceived soreness were assessed before and after every session. To compare changes in the primary training outcomes between conditions (i.e., elbow flexor cross-sectional area, muscle thickness, isometric force, dynamic strength, and arm circumference), Bayesian linear mixed effect models were constructed to mimic an analysis of covariance (i.e., ANCOVA) with an adjustment for the baseline score of the dependent variable. To compare longitudinal trends in the subjective perceptions of fatigue (i.e., session RPE and perceived elbow flexor soreness) between conditions Bayesian linear mixed effect models with a Gaussian response distribution were fit. For parameters of interest from each model (i.e., marginal effects for condition or the two-way interaction between condition and site, exercise, or session), draws were taken from the posterior distribution to construct a probability density function (i.e., mode and associated highest density intervals) that was used to make probabilistic inferences. The probability density functions related to the primary research questions were also compared to a region of practical equivalence (ROPE) defined by the typical error of measurement. RESULTS: Changes in total CSA for both LONG (6.01 cm2 [95% HDI: -1.64, 14.66], 80.12% probability > ROPE) and MIXED (3.18 cm2 [95% HDI: -5.66, 12.69], 55.51% probability > ROPE) were considered meaningful, but the contrast between conditions (2.58 cm2 [HDI: -4.1, 9.01], 48.96% probability > ROPE) was not meaningful. Contrast estimates in arm circumference were meaningfully greater for the LONG condition at proximal (0.33 mm [95% HDI: -0.92, 1.95], 52.19% probability > ROPE), middle (0.46 mm [95% HDI: -1.06, 1.9], 54.39% probability > ROPE), and distal (0.89 mm [95% HDI: -0.74, 2.4], 74.26% probability > ROPE) regions of the upper arm. Changes in dynamic strength for both conditions in the shortened cable curl (LONG=3.67 kg [95% HDI: -0.77, 7.65], 76.99% probability > ROPE; MIXED=5.44 kg [95% HDI: 0.59, 9.78], 92.31% probability > ROPE) and lengthened cable curl (LONG=6.93 kg [95% HDI: 2.37, 11.86], 97.86% probability > ROPE; MIXED=6.57 kg [95% HDI: 0.35, 11.77]; 93.86% probability > ROPE) were considered meaningful, but the contrast between conditions was not meaningful. Changes in regional MT, regional isometric force, total isometric strength, sRPE and perceived soreness were not considered meaningful for either condition. CONCLUSIONS:  Given the lack of meaningful differences between conditions and the questionable relevance of circumference measurements, It seems that neither training condition provides clearly superior outcomes for hypertrophy, strength, or perceptual fatigue

The Effect of Resistance Training Proximity to Failure on Muscular Adaptations and Longitudinal Fatigue in Trained Men

Purpose: This study examined the effect of proximity to failure on hypertrophy, strength, and fatigue. We hypothesized strength gains would be superior in non-failure groups compared to those that include sets to momentary failure, while hypertrophy would be similar in all groups. Methods: 38 men were randomized into four groups (4–6 rating of perceived exertion-RPE per set, 7–9 RPE per set, 7–9+ RPE [last set taken to momentary failure], and 10 RPE per set) and completed an eight-week program. Back squat and bench press strength, muscle thickness, subjective fatigue, muscle soreness, and biomarkers (creatine kinase-CK and lactate dehydrogenase-LDH) were assessed. Results: Bench Press strength gains were comparable between the 4–6 RPE (9.05 kg [95% CI: 6.36, 11.76]) and 7–9 RPE (9.72 kg [95% CI: 7.03, 12.42]) groups, while outcomes in the 7–9+ (5.07 kg [95% CI: 2.05, 8.1]) and 10 RPE (0.71 kg [95% CI: -4.51, 5.54]) groups were slightly inferior. Squat strength gains were comparable between 4–6 RPE (13.79 kg [95% CI: 7.54, 19.92]) and 7–9 RPE (18.05 kg [95% CI: 12.28, 23.99]) groups, but data for 7–9+ RPE and 10 RPE are difficult to interpret due to poor feasibility of the protocols. For muscle hypertrophy, our data do not provide strong conclusions as to the effects of proximity to failure due to the large variability observed. The indices of fatigue were largely comparable between groups, without strong evidence of the repeated bout effect. Conclusion: These data suggest strength outcomes are comparable when taking sets to either a self-reported 4–6 RPE or 7–9 RPE, while training that includes sets to momentary failure may result in slightly inferior outcomes (i.e., 7–9+ and 10 RPE). However, the influence of proximity to failure on hypertrophy remains unclear and our data did not reveal clear differences between groups in any measure of fatigue

Conditional over-expression of RAGE by embryonic alveolar epithelium compromises the respiratory membrane and impairs endothelial cell differentiation

Abstract Background Receptors for advanced glycation end-products (RAGE) are cell surface receptors prominently expressed by lung epithelium. Previous research demonstrated that over-expression of RAGE by murine alveolar epithelial cells during embryogenesis caused severe lung hypoplasia and neonatal lethality. However, the effects of RAGE over-expression on adjacent matrix and endothelial cells remained unknown. Methods RAGE transgenic (TG) mice were generated that conditionally over-expressed RAGE in alveolar type II cells when fed doxycycline (dox) from conception to E18.5. To evaluate effects on the basement membrane, immunostaining and immunoblotting were performed for collagen IV and MMP-9, a matrix metalloprotease capable of degrading basement membranes. To assess changes in vasculature, immunostaining, immunoblotting and qRT-PCR were performed for Pecam-1, a platelet endothelial cell adhesion marker also known as CD31. Lastly, to characterize potential regulatory mechanisms of endothelial cell differentiation, immunoblotting and qRT-PCR for FoxM1, a key endothelium-specific transcription factor of the Forkhead Box (Fox) family, were completed. Results Qualitative immunostaining for collagen IV was less in RAGE TG mice compared to controls and immunoblotting revealed decreased collagen IV in the RAGE TG mouse lung. Additionally, elevated MMP-9 detected via immunostaining and immunoblotting implicated MMP-9 as a possible down stream effector in matrix destabilization mediated by RAGE signaling. Lastly, Pecam-1 assessment revealed a decrease in the prevalence of microvascular endothelial cells coincident with FoxM1 abrogation in RAGE TG mice compared to controls. Conclusions RAGE over-expression by alveolar epithelium weakened the basement membrane and associated matrix via increased MMP-9 activity. Furthermore, over-expression of RAGE inhibited FoxM1, suggesting that anomalous transcriptional control contributes to decreased endothelial cell prevalence in the TG mouse lung. </jats:sec

An intergenerational study of perceptions of changes in active free play among families from rural areas of Western Canada

Background: Children's engagement in active free play has declined across recent generations. Therefore, the purpose of this study was to examine perceptions of intergenerational changes in active free play among families from rural areas. We addressed two research questions: (1) How has active free play changed across three generations? (2) What suggestions do participants have for reviving active free play? Methods: Data were collected via 49 individual interviews with members of 16 families (15 grandparents, 16 parents, and 18 children) residing in rural areas/small towns in the Province of Alberta (Canada). Interview recordings were transcribed verbatim and subjected to thematic analysis guided by an ecological framework of active free play. Results: Factors that depicted the changing nature of active free play were coded in the themes of less imagination/more technology, safety concerns, surveillance, other children to play with, purposeful physical activity, play spaces/organized activities, and the good parenting ideal. Suggestions for reviving active free play were coded in the themes of enhance facilities to keep kids entertained, provide more opportunities for supervised play, create more community events, and decrease use of technology. Conclusions: These results reinforce the need to consider multiple levels of social ecology in the study of active free play, and highlight the importance of community-based initiatives to revive active free play in ways that are consistent with contemporary notions of good parentin