The Anthropometry of Economical Running.

The influence of anthropometry and body composition on running economy is unclear, with previous investigations involving small relatively homogeneous groups of runners and limited anthropometric/composition measurements. PURPOSE: To comprehensively investigate the relationships of anthropometry and body composition with running economy within a large heterogeneous sample of runners. METHODS: Eighty-five runners (males [M], n = 45; females [F], n = 40), of diverse competitive standard, performed a discontinuous protocol of incremental treadmill running (4-min stages, 1 km·h increments) to establish locomotory energy cost (LEc) of running at submaximal speeds (averaged across 10-12 km·h; the highest common speed < lactate turnpoint). Measurements of anthropometry, including segment lengths, perimeters, masses and moments of inertia, and body composition were obtained using tape-based measurements and dual-energy x-ray absorptiometry. RESULTS: Absolute LEc (ABSLEc, kcal·km) was positively correlated with 21 (of 27) absolute anthropometric variables in both male and female cohorts. Multiple-regression analyses revealed that one variable (mean perimeter z score) explained 49.4% (M) and 68.9% (F) of the variance in ABSLEc. Relative LEc (RELLEc, kcal·kg·km) was also correlated with five (M) and seven (F) normalized anthropometric variables, and regression analyses explained 31.6% (M; percentage bone mass and normalized hip perimeter) and 33.3% (F, normalized forearm perimeter) of the variance in RELLEc. CONCLUSIONS: These findings provide novel and robust evidence that anthropometry and body composition variables, predominantly indicative of relative slenderness, explain a considerable proportion of the variance in running economy (i.e., more slender, lower energy cost). We, therefore, recommend that runners and coaches are attentive to relative slenderness in selecting and training athletes with the aim of enhancing running economy, and improving distance running performance.

The influence of model parameters on model validation.

The study examined the sensitivity of two musculoskeletal models to the parameters describing each model. Two different models were examined: a phenomenological model of human jumping with parameters based on live subject data, and the second a model of the First Dorsal Interosseous with parameters based on cadaveric measurements. Both models were sensitive to the model parameters, with the use of mean group data not producing model outputs reflective of either the performance of any group member or the mean group performance. These results highlight the value of subject specific model parameters, and the problems associated with model validation.