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Should We Seek for Generalized Standards in Bike Fitting?

Rico Bini, Rodrigo PhD

Journal of Strength and Conditioning Research: March 2013 - Volume 27 - Issue 3 - p E1
doi: 10.1519/JSC.0b013e318260061b
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Biomechanical Laborabory,Brazilian Institute of Leather Technology, Footwear, and Artifacts, Novo Hamburgo, Brazil

Bike fit is an increasing industry in sports sciences and has received more attention from experimental research during the last few years (2,4–6). Two articles have been recently accepted for publication in the Journal of Strength and Conditioning Research. The first one (A kinematic comparison of alterations to knee and ankle angles from resting measures to active pedaling during a graded exercise protocol) (5) provided evidence that knee flexion angles are affected by workload level during cycling. Although the authors highlighted that individual responses should be on focus for bike fitting, another article (influence of saddle height on lower limb kinematics in well-trained cyclists) (2) walks in a completely different avenue. These authors provided a standardized model of setting “optimal saddle height” based on kinematic data taken from professional cyclists. From what I could read from the study of Peveler et al. (5), it is not logical to set cyclists in a standard saddle height. Evidence has shown that changes in saddle height <5% of lower leg length do not affect cycling performance or injury risk (1).

Along with that, the statistical methods used by Ferrer-Roca et al. (2) are very confusing. It is not clear how the authors could ensure a Gaussian distribution of the results using a Kolmogorov-Smirnov test. They probably assessed Gaussian distribution of their data with no reports on how they solved nonuniform distribution. The key issue is on the use of the multivariate linear regression to predict saddle height based on kinematic and anthropometric data. There is no information on criteria for inclusion and exclusion of variables in the statistical model. A Stepwise method would be recommended for including or excluding variables from the model. For the type of analysis conducted by the authors (multivariate linear regression), it has been recommended that a larger sample size be used (3). There is no reference on how sample size was determined for this type of analysis.

These questions should be clarified by the authors; then the strength of evidence provided in this study can be assessed and the methods provided by the authors could be used for a clinical perspective.

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References

1. Bini RR, Hume PA, Croft JL. Effects of bicycle saddle height on knee injury risk and cycling performance. Sports Med 41: 463–476, 2011.
2. Ferrer-Roca V, Roig A, Galilea P, García-López J. Influence of saddle height on lower limb kinematics in well-trained cyclists: Static versus dynamic evaluation in bike fitting. J Strength Cond Res. In press.
3. Hsieh FY, Bloch DA, Larsen MD. A simple method of sample size calculation for linear and logistic regression. Stat Med 17: 1623–1634, 1998.
4. Korff T, Fletcher G, Brown D, Romer LM. Effect of “pose” cycling on efficiency and pedaling mechanics. Eur J Appl Physiol. 111: 1177–1186, 2011.
5. Peveler WW, Shew B, Johnson S, Palmer TG. A kinematic comparison of alterations to knee and ankle angles from resting measures to active pedaling during a graded exercise protocol. J Strength Cond Res. In press.
6. Ramos Ortega J, Munuera PV, Dominguez G. Antero-posterior position of the cleat for road cycling. Sci Sports. In press.
© 2013 National Strength and Conditioning Association