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PeerJ. 2018 Jun 27;6:e5071. doi: 10.7717/peerj.5071. eCollection 2018.

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

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Department of Biomedical Engineering, Northwestern University, Evanston, IL, United States of America.
Department of Health Sciences, City University of New York, Herbert H. Lehman College, Bronx, NY, United States of America.
School of Biomedical Sciences, University of Queensland, St. Lucia, Queensland, Australia.



The 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.


Data 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.


The 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).


Methods 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.


Analysis of covariance; Hierarchical linear models; Hypertrophy; Regression; Repeated measures; Strength

Conflict of interest statement

The authors declare there are no competing interests.

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