 For the initial biomechanical analyses, we have chosen to focus on Hypothesis 1.4 with the use Latent Profile Analysis LPA. We will use LPA to examine whether we can cluster subjects with similar characteristics of the GRFv, HAdT, hip moments minimum and maximum, lateral trunk motion and center of gravity displacement into distinct neuromuscular profiles. Our latent profile analyses will evaluate independent variables across the multiple tasks to form groups of girls with similar neuromuscular patterns for these variables where the heterogeneity of response pattern is minimized within each profile and maximized across profiles. Initially, two profiles are specified for the LPA model, then, in a stepwise fashion, the number of profiles specified is increased by one. At each step, changes in Bayesian information criteria BIC, adjusted for sample size, is used to assess model fit and identify the number of profiles needed. The point at which the number of profiles is deemed adequate is when no significant drop in BIC is seen when the profile number is increased. In addition, the Lo-Mendell-Rubin adjusted likelihood ratio test is used to determine the optimal number of profiles.Lo 2001 The analysis was implemented using Mplus 5.Muthen 2007 Validation of profile group includes examination as an independent predictor of LOAD. 