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Sports Medicine

, Volume 44, Issue 10, pp 1439–1458 | Cite as

The Effect of Exercise Training on Lower Trunk Muscle Morphology

  • Behnaz Shahtahmassebi
  • Jeffrey J. HebertEmail author
  • Norman J. Stomski
  • Mark Hecimovich
  • Timothy J. Fairchild
Systematic Review

Abstract

Background

Skeletal muscle plays an important role in maintaining the stability of the lumbar region. However, there is conflicting evidence regarding the effects of exercise on trunk muscle morphology.

Objective

To systematically review the literature on the effects of exercise training on lower trunk muscle morphology to determine the comparative effectiveness of different exercise interventions.

Data Source and Study Selection

A systematic search strategy was conducted in the following databases: PubMed, SportDiscus, CINAHL, the Cochrane Library and PEDro. We included full, peer-reviewed, prospective longitudinal studies, including randomized controlled trials and single-group designs, such as pre- to post-intervention and crossover studies, reporting on the effect of exercise training on trunk muscle morphology.

Study Appraisal and Synthesis

Study quality was assessed with the Cochrane risk-of-bias tool. We classified each exercise intervention into four categories, based on the primary exercise approach: motor control, machine-based resistance, non-machine-based resistance or cardiovascular. Treatment effects were estimated using within-group standardized mean differences (SMDs).

Results

The systematic search identified 1,911 studies; of which 29 met our selection criteria: motor control (n = 12), machine-based resistance (n = 10), non-machine-based resistance (n = 5) and cardiovascular (n = 2). Fourteen studies (48 %) reported an increase in trunk muscle size following exercise training. Among positive trials, the largest effects were reported by studies testing combined motor control and non-machine-based resistance exercise (SMD [95 % CI] = 0.66 [0.06 to 1.27] to 3.39 [2.80 to 3.98]) and machine-based resistance exercise programmes (SMD [95 % CI] = 0.52 [0.01 to 1.03] to 1.79 [0.87 to 2.72]). Most studies investigating the effects of non-machine-based resistance exercise reported no change in trunk muscle morphology, with one study reporting a medium effect on trunk muscle size (SMD [95 % CI] = 0.60 [0.03 to 1.16]). Cardiovascular exercise interventions demonstrated no effect on trunk muscle morphology (SMD [95 % CI] = −0.16 [−1.14 to 0.81] to 0.09 [−0.83 to 1.01]).

Limitations

We excluded studies published in languages other than English, and therefore it is possible that the results of relevant studies are not represented in this review. There was large clinical heterogeneity between the included studies, which prevented data synthesis. Among the studies included in this review, common sources of potential bias were random sequence generation, allocation concealment and blinding. Finally, the details of the exercise parameters were poorly reported in most studies.

Conclusion

Approximately half of the included studies reported an increase in lower trunk muscle size following participation in an exercise programme. Among positive trials, studies involving motor control exercises combined with non-machine-based resistance exercise, as well as machine-based resistance exercises, demonstrated medium to large effects on trunk muscle size. Most studies examining the effect of non-machine-based resistance exercise and all studies investigating cardiovascular exercise reported no effect on trunk muscle morphology. However, these results should be interpreted with caution because of the substantial risk of bias and suboptimal reporting of exercise details in the included studies. Additional research, using methods ensuring a low risk of bias, are required to further elucidate the effects of exercise on trunk muscle morphology.

Keywords

Exercise Training Resistance Exercise Exercise Intervention Trunk Muscle Cardiovascular Exercise 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors would like to thank Ms Margaret Solosy for assistance with developing the search strategy, Dr Golnaz Shahtahmassebi for statistical advice and Mr Andrew Schechter (A.S.) for assisting with study selection. The contributions of the authors are as follows: B.S.—study conception and design, data acquisition, analysis and interpretation, drafting and final approval of the manuscript; J.J.H.—study conception and design, data interpretation, critical revision and approval of the final manuscript; N.J.S.—data acquisition, critical revision and final approval of the manuscript; M.H.—study conception, critical revision and final approval of the manuscript; T.J.F.—study conception and design, data interpretation, critical revision and final approval of the manuscript.

Conflicts of interest

The authors have no conflicts of interest that are directly relevant to the content of this review. No sources of funding were used in the preparation of this review.

Supplementary material

40279_2014_213_MOESM1_ESM.docx (15 kb)
Supplementary material 1 (DOCX 15 kb)

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Behnaz Shahtahmassebi
    • 1
  • Jeffrey J. Hebert
    • 1
    Email author
  • Norman J. Stomski
    • 2
  • Mark Hecimovich
    • 1
  • Timothy J. Fairchild
    • 1
  1. 1.School of Psychology and Exercise ScienceMurdoch UniversityPerthAustralia
  2. 2.School of Health ProfessionsMurdoch UniversityPerthAustralia

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