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Causal Mediation Analysis Could Resolve Whether Training-Induced Increases in Muscle Strength are Mediated by Muscle Hypertrophy

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Abstract

Resistance training increases muscle size (i.e., causes hypertrophy) and muscle strength, particularly in untrained individuals. Hypertrophy is widely believed to be one of the mechanisms (i.e., a mediator) by which resistance training increases strength. However, some researchers have questioned whether training-induced hypertrophy causes increases in strength. One approach to resolving this issue has been to use correlations between training-induced changes in muscle size and strength to infer the effect of hypertrophy on strength. This is problematic because correlations between changes in muscle size and strength may be confounded (i.e., correlation is not causation). Another approach has involved randomizing participants to different volumes of exercise to create different levels of hypertrophy and then comparing the strength increases associated with different levels of hypertrophy. This approach is also problematic because the unit of randomization is exercise volume rather than hypertrophy, and the potential for confounding remains. Thus, a new approach is needed to determine the extent to which hypertrophy increases muscle strength. Here, we introduce resistance training researchers to causal mediation analysis and recommend that it be used to resolve the current debate. Causal mediation analysis potentially provides an unconfounded estimate of the effect of a mediating variable (hypertrophy) on an outcome (strength). This analysis is supplemented by causal maps that help conceptualize research questions and identify potential confounders. In addition to resolving the debate on hypertrophy, causal mediation analysis can be used to answer a host of other questions about mechanisms in the health sciences.

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References

  1. Balshaw TG, Massey GJ, Maden-Wilkinson TM, Morales-Artacho AJ, McKeown A, Appleby CL, et al. Changes in agonist neural drive, hypertrophy and pre-training strength all contribute to the individual strength gains after resistance training. Eur J Appl Physiol. 2017;117(4):631–40.

    Article  PubMed  Google Scholar 

  2. Balshaw TG, Massey CD, Maden-Wilkinson TM, Folland JP. Muscle size and strength: debunking the “completely separate phenomena” suggestion. Eur J Appl Physiol. 2017;117(6):1275–6.

    Article  PubMed  Google Scholar 

  3. Buckner SL, Dankel SJ, Mattocks KT, Jessee MB, Mouser JG, Counts BR, et al. The problem of muscle hypertrophy: revisited. Muscle Nerve. 2016;54(6):1012–4.

    Article  PubMed  Google Scholar 

  4. Buckner SL, Dankel SJ, Mattocks KT, Jessee MB, Mouser JG, Loenneke JP. Muscle size and strength: another study not designed to answer the question. Eur J Appl Physiol. 2017;117(6):1273–4.

    Article  PubMed  Google Scholar 

  5. Dankel SJ, Buckner SL, Jessee MB, Mouser JG, Mattocks KT, Abe T, et al. Correlations do not show cause and effect: not even for changes in muscle size and strength. Sports Med. 2018;48(1):1–6.

    Article  PubMed  Google Scholar 

  6. Erskine RM, Fletcher G, Folland JP. The contribution of muscle hypertrophy to strength changes following resistance training. Eur J Appl Physiol. 2014;114(6):1239–49.

    Article  PubMed  Google Scholar 

  7. Mattocks KT, Buckner SL, Jessee MB, Dankel SJ, Mouser JG, Loenneke JP. Practicing the test produces strength equivalent to higher volume training. Med Sci Sports Exerc. 2017;49(9):1945–54.

    Article  PubMed  Google Scholar 

  8. Pearl J, Glymour M, Jewell NP. Causal inference in statistics: a primer. Chichester: Wiley; 2016.

    Google Scholar 

  9. Dankel SJ, Counts BR, Barnett BE, Buckner SL, Abe T, Loenneke JP. Muscle adaptations following 21 consecutive days of strength test familiarization compared with traditional training. Muscle Nerve. 2017;56(2):307–14.

    Article  PubMed  Google Scholar 

  10. Pirlott AG, MacKinnon DP. Design approaches to experimental mediation. J Exp Soc Psychol. 2016;66:29–38.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Valeri L, VanderWeele TJ. Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros. Psychol Methods. 2013;18(2):137–50.

    Article  PubMed  PubMed Central  Google Scholar 

  12. VanderWeele TJ, Shpitser I. On the definition of a confounder. Ann Stat. 2013;41(1):196–220.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Pearl J, Mackenzie D. The book of why: the new science of cause and effect. New York: Basic Books; 2018.

    Google Scholar 

  14. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–82.

    Article  CAS  PubMed  Google Scholar 

  15. Imai K, Keele L, Tingley D. A general approach to causal mediation analysis. Psychol Methods. 2010;15(4):309–34.

    Article  PubMed  Google Scholar 

  16. Pearl J. Interpretation and identification of causal mediation. Psychol Methods. 2014;19(4):459–81.

    Article  PubMed  Google Scholar 

  17. Forte R, Boreham CA, Leite JC, De Vito G, Brennan L, Gibney ER, et al. Enhancing cognitive functioning in the elderly: multicomponent vs resistance training. Clin Interv Aging. 2013;8:19–27.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Mavros Y, Gates N, Wilson GC, Jain N, Meiklejohn J, Brodaty H, et al. Mediation of cognitive function improvements by strength gains after resistance training in older adults with mild cognitive impairment: outcomes of the study of mental and resistance training. J Am Geriatr Soc. 2017;65(3):550–9.

    Article  PubMed  Google Scholar 

  19. Cresswell SL, Eklund RC. Motivation and burnout among top amateur rugby players. Med Sci Sports Exerc. 2005;27(3):469–77.

    Article  Google Scholar 

  20. Gomes AR, Faria S, Vilela C. Anxiety and burnout in young athletes: the mediating role of cognitive appraisal. Scand J Med Sci Sports. 2017;27(12):2116–26.

    Article  CAS  PubMed  Google Scholar 

  21. McNeill LH, Wyrwich KW, Brownson RC, Clark EM, Kreuter MW. Individual, social environmental, and physical environmental influences on physical activity among black and white adults: a structural equation analysis. Ann Behav Med. 2006;31(1):36–44.

    Article  PubMed  Google Scholar 

  22. Bollen KA, Pearl J. Eight myths about causality and structural equation models. In: Morgan SL, editor. Handbook of causal analysis for social research. Dordrecht: Springer; 2013.

    Google Scholar 

  23. Tarka P. An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences. Qual Quant. 2018;52(1):313–54.

    Article  PubMed  Google Scholar 

  24. Shrier I. Understanding causal inference: the future direction in sports injury prevention. Clin J Sports Med. 2007;17(3):220–4.

    Article  Google Scholar 

  25. Attia JR, Oldmeadown C, Holliday EG, Jones MP. Deconfounding confounding part 2: using directed acyclic graphs (DAGs). Med J Aust. 2017;206(11):480–3.

    Article  PubMed  Google Scholar 

  26. Cole SR, Hernan MA. Fallibility in estimating direct effects. Int J Epidemiol. 2002;31(1):163–5.

    Article  PubMed  Google Scholar 

  27. Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology. 1999;10:37–48.

    Article  CAS  PubMed  Google Scholar 

  28. Jewell NP. Statistics for epidemiology. Boca Raton: Taylor & Francis; 2004.

    Google Scholar 

  29. Sauer B, VanderWeele TJ. Supplement 2. Use of directed acylic graphs. In: Developing a protocol for observational comparative effectiveness research: a user’s guide. Rockville: Agency for Healthcare Research and Quality; 2013. pp. 177–83.

  30. Shrier I, Platt RW. Reducing bias through directed acyclic graphs. BMC Med Res Methodol. 2008;8:70.

    Article  PubMed  PubMed Central  Google Scholar 

  31. VanderWeele TJ. Mediation analysis: a practioner’s guide. Annu Rev Public Health. 2016;37:17–32.

    Article  PubMed  Google Scholar 

  32. Textor J, van der Zander B, Gilthorpe MS, Liskiewicz M, Ellison GT. Robust causal inference using directed acyclic graphs: the R package ‘dagitty’. Int J Epidemiol. 2016;45(6):1887–94.

    PubMed  Google Scholar 

  33. Textor J, Hardty J, Knuppel S. DAGitty: a graphical tool for analyzing causal diagrams. Epidemiology. 2011;22(5):745.

    Article  PubMed  Google Scholar 

  34. Hicks R, Tingley D. Causal mediation analysis. Stata J. 2011;11(4):605–19.

    Article  Google Scholar 

  35. Tingley D, Yamamoto T, Hirose K, Keele L, Imai K. Mediation: R package for causal mediation analysis. J Stat Softw. 2014;59(5):1–38.

    Article  Google Scholar 

  36. Hubal MJ, Gordish-Dressman H, Thompson PD, Price TB, Hoffman EP, Angelopoulos TJ, et al. Variability in muscle size and strength gain after unilateral resistance training. Med Sci Sports Exerc. 2005;37(6):964–72.

    PubMed  Google Scholar 

  37. O’Brien TD, Reeves ND, Baltzopoulos V, Jones DA, Maganaris CN. In vivo measurements of muscle specific tension in adults and children. Exp Physiol. 2010;95(1):202–10.

    Article  PubMed  Google Scholar 

  38. Damas F, Phillips SM, Lixandrão ME, Vechin FC, Libardi CA, Roschel H, et al. Early resistance training-induced increases in muscle cross-sectional area are concomitant with edema-induced muscle swelling. Eur J Appl Physiol. 2016;116(1):49–56.

    Article  PubMed  Google Scholar 

  39. Damas F, Phillips SM, Lixandrão ME, Vechin FC, Libardi CA, Roschel H, et al. An inability to distinguish edematous swelling from true hypertrophy still prevents a completely accurate interpretation of the time course of muscle hypertrophy. Eur J Appl Physiol. 2016;116(2):445–6.

    Article  PubMed  Google Scholar 

  40. Bolsterlee B, Gandevia SC, Herbert RD. Effect of transducer orientation on errors in ultrasound image-based measurements of human medial gastrocnemius muscle fascicle length and pennation. PLoS One. 2016;11(6):e0157273.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Fukunaga T, Roy RR, Shellock FG, Hodgson JA, Day MK, Lee PL, et al. Physiological cross-sectional area of human leg muscles based on magnetic resonance imaging. J Orthop Res. 1992;10(6):928–34.

    Article  CAS  PubMed  Google Scholar 

  42. Reeves ND, Narici MV, Maganaris CN. Effect of resistance training on skeletal muscle-specific force in elderly humans. J Appl Physiol. 2004;96(3):885–92.

    Article  CAS  PubMed  Google Scholar 

  43. Farina D, Merletti R, Enoka RM. The extraction of neural strategies from the surface EMG. J Appl Physiol. 2004;96(4):1486–95.

    Article  PubMed  Google Scholar 

  44. Keenan KG, Farina D, Maluf KS, Merletti R, Enoka RM. Influence of amplitude cancellation on the simulated surface electromyogram. J Appl Physiol. 2005;98(1):120–31.

    Article  PubMed  Google Scholar 

  45. Gandevia SC. Spinal and supraspinal factors in human muscle fatigue. Physiol Rev. 2001;81(4):1725–89.

    Article  CAS  PubMed  Google Scholar 

  46. Nuzzo JL, Taylor JL, Gandevia SC. CORP: measurement of upper and lower limb muscle strength and voluntary activation. J Appl Physiol. 2019;126(3):513–43.

    Article  PubMed  Google Scholar 

  47. Taylor JL. Point: the interpolated twitch does/does not provide a valid measure of the voluntary activation of muscle. J Appl Physiol. 2009;107(1):354–5.

    Article  PubMed  Google Scholar 

  48. Todd G, Taylor JL, Gandevia SC. Measurement of voluntary activation based on transcranial magnetic stimulation over the motor cortex. J Appl Physiol. 2016;121(3):678–86.

    Article  PubMed  Google Scholar 

  49. Tchetgen Tchetgen EJ, VanderWeele TJ. Identification of natural direct effects when a confounder of the mediator is directly affected by exposure. Epidemiology. 2014;25(2):282–91.

    Article  PubMed  Google Scholar 

  50. VanderWeele TJ, Vansteelandt S. Mediation analysis with multiple mediators. Epidemiol Methods. 2014;2(1):95–115.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Whittle R, Mansell G, Jellema P, van der Windt D. Applying causal mediation methods to clinical trial data: What can we learn about why our interventions (don’t) work? Eur J Pain. 2017;21(4):614–22.

    Article  CAS  PubMed  Google Scholar 

  52. Blazevich AJ, Gill ND, Deans N, Zhou S. Lack of human muscle architectural adaptation after short-term strength training. Muscle Nerve. 2007;35(1):78–86.

    Article  PubMed  Google Scholar 

  53. Hendy AM, Kidgell DJ. Anodal tDCS applied during strength training enhances motor cortical plasticity. Med Sci Sports Exerc. 2013;45(9):1721–9.

    Article  PubMed  Google Scholar 

  54. Weier AT, Pearce AJ, Kidgell DJ. Strength training reduces intracortical inhibition. Acta Physiol. 2012;206(2):109–19.

    Article  CAS  Google Scholar 

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Correspondence to James L. Nuzzo.

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James Nuzzo and Robert Herbert are supported by the National Health Medical Research Council of Australia. Harrison Finn is supported by an Australian Postgraduate Award.

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James Nuzzo, Harrison Finn, and Robert Herbert have no conflicts of interest that are directly relevant to the content of this article.

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Nuzzo, J.L., Finn, H.T. & Herbert, R.D. Causal Mediation Analysis Could Resolve Whether Training-Induced Increases in Muscle Strength are Mediated by Muscle Hypertrophy. Sports Med 49, 1309–1315 (2019). https://doi.org/10.1007/s40279-019-01131-8

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