Methods matter: the relationship between strength and hypertrophy depends on methods of measurement and analysis

Abstract

PurposeThe relationship between changes in muscle size and strength may be affected by both measurement and statistical approaches, but their effects have not been fully considered or quantified. Therefore, the purpose of this investigation was to explore how different methods of measurement and analysis can affect inferences surrounding the relationship between hypertrophy and strength gain.MethodsData from a previous study—in which participants performed eight weeks of elbow flexor training, followed by an eight-week period of detraining—were reanalyzed using different statistical models, including standard between-subject correlations, analysis of covariance, and hierarchical linear modeling.ResultsThe associative relationship between strength and hypertrophy is highly dependent upon both method/site of measurement and analysis; large differences in variance accounted for (VAF) by the statistical models were observed (VAF = 0–24.1%). Different sites and measurements of muscle size showed a range of correlations coefficients with one another (r = 0.326–0.945). Finally, exploratory analyses revealed moderate-to-strong relationships between within-individual strength-hypertrophy relationships and strength gained over the training period (ρ = 0.36–0.55).ConclusionsMethods of measurement and analysis greatly influence the conclusions that may be drawn from a given dataset. Analyses that do not account for inter-individual differences may underestimate the relationship between hypertrophy and strength gain, and different methods of assessing muscle size will produce different results. It is suggested that robust experimental designs and analysis techniques, which control for different mechanistic sources of strength gain and inter-individual differences (e.g., muscle moment arms, muscle architecture, activation, and normalized muscle force), be employed in future investigations.

To Flex or Rest: Does Adding No-Load Isometric Actions to the Inter-Set Rest Period in Resistance Training Enhance Muscular Adaptations? A Randomized-Controlled Trial

“…This may be explained, at least in part, by the methods used to assess muscle growth. Specifically, evidence indicates that MT does not show a high correlation with maximal strength (Vigotsky et al, 2018). Moreover, differences in quadriceps hypertrophy were limited to only the mid-thigh at the location of the rectus femoris.…”

Exercise-Induced Changes in Muscle Size do not Contribute to Exercise-Induced Changes in Muscle Strength

“…Would correlations from longer term studies on the changes in skinfold thickness and muscle strength be enough [47,48]? It is hard to imagine another scenario where correlations (between or within), in the absence of experimental evidence, are sufficient to make causal claims about the importance of one variable for another variable [40,49]. If muscle growth is a meaningful contributor for strength adaptation, then this should be demonstrated through experiments.…”

Exercise-Induced Myofibrillar Hypertrophy is a Contributory Cause of Gains in Muscle Strength

“…Finally, while the studies presented hitherto address the question of whether those who gain more muscle also get stronger (between-subject), it has been suggested that the question of greater interest is if an individual will get stronger as they gain more muscle (within-subject) [42]. Indeed, such analyses explain a much greater percentage of variance in strength gain than do between-subject analyses [42,43]. While this work remains in its infancy and has room for improvement, both methodologically and statistically, we believe the early results to be both intriguing and thought-provoking in helping to elucidate the strengthhypertrophy relationship.…”

“…Since an experiment that assesses all potential mechanisms would be nearly impossible to complete in humans, multiple lines of work may be needed to establish or refute hypertrophy as a contributory cause. That is, the question may not be able to be answered through a single experiment, but rather, many experiments combined with modeling may be needed [42].…”